This subject aims to introduce students to the application of programming and computational methods to solve problems in the context of bioengineering research and industry. It introduces students to the fundamentals of software programming and computational methods via the use of programming languages, such as MATLAB and Python. These techniques will be explored in the context of problems drawn from different aspects of bioengineering including, but not restricted to, fluid mechanics, image processing, electromagnetism, control systems, biomechanics, biomaterials, biosignals and clinical statistics.

AIMS

This subject introduces students to the fundamental principles of circuit and signal measurements and analyses in a biosignals context. In addition to the fundamental concepts, topics to be covered include an introduction to various types of sensors and the basic methods required to analyse measurements, calibrate sensors and evaluate measurement system performance.

In the laboratories, students will learn about laboratory safety, team work and measurement safety in an integrated way.

This subject is one of the subjects that define the Bioengineering Systems Major in the Bachelor of Science and Bachelor of Biomedicine, and it is a core requirement for the Master of Engineering (Biomedical). It provides a foundation for various subsequent subjects, including BMEN90002 Neural Information Processing and BMEN90021 Medical Imaging.

INDICATIVE CONTENT

Topics include:

Basic principles of charge, current, Coulomb's law, electric fields and electrical energy, Kirchhoff's current law, Kirchhoff's voltage law, voltage and current division, node voltage analysis, mesh current analysis, Thévenin and Norton equivalent circuits, transient analysis of RC and RL circuits, steady-state analysis of RLC circuits, phasors and impedance, frequency domain models for signals and frequency response for systems, continuous-time and discrete-time Fourier transforms, frequency response, filtering, transfer functions, Z-transforms, Laplace transforms, poles and zeros, Bode plots, and the relationship to state-space representations.

This material is complemented by the use of software tools (e.g. MATLAB) for computation and simulation, and practical experience with circuits and systems in the laboratory.

AIMS

This subject involves undertaking biosystems design group projects from concept to reporting and communicating the design proposal through to possible development. This subject will prepare students for employment in the health and medical technology design and development industries. The emphasis of each of the projects is associated with a well-defined project description. The open-ended nature of the design task will result in students having exposure to requirements for design and development of medical devices including ethics, safety and risk assessment, common sensors to detect medically relevant biomedical signals, and acquisition, amplification and processing of biomedical sensor signals.

The subject will provide an integrated capstone experience for the Bioengineering major.

INDICATIVE CONTENT

Topics include:

• Design control processes -design and development planning, design input, design control, design output, design review, and design verification.
• Theory of measurement – understanding and applying the limitations of measurement.
• Amplifier circuits –design and construct basic op-amp circuits to the application of high precision instrumentation amps.
• Data acquisition systems – programming and applying industry standard engineering software and hardware tools.
• Sensors – adapting and implementing simple displacement and electrochemical sensors.
• Physiological dynamics – understanding physiological dynamic parameters and applying parameter estimation techniques to acquire physiological signals.
• Non-invasive physiological system – use of sensors, amplifiers, data acquisition systems and parameter estimation to design and construct a physiological system.

This subject is designed to enable students to apply the fundamental principles of material sciences to biomedical applications. It will introduce different materials (polymers, metals, ceramics and composites) and their behaviours in contact with biological environments. In addition, students will learn about the properties of biological materials like bone, muscles, skin and vasculature.

Critical Communication for Engineers (CCE) addresses the skills vital for professional success. Problem analysis skills and being able to present solutions effectively to your engineering peers, leaders and the broader community are a powerful combination. These are the focus of CCE.

They are challenging skills to learn—and you will likely work to improve them throughout your career. Effective communication is not merely about how to write a report or to give a formal presentation. Developing a strong argument—having something insightful to communicate—is essential for capturing the attention of an audience. This requires developing good interpersonal skills for gathering information and testing ideas.

The subject is divided into four ‘topics’ presented in sequence through the semester. Each topic is self-contained and dedicated to a different engineering issue. There is an assessment for each topic, meaning that you will be able to apply what you have learned from one topic to the following topics. This way, you will have a lot of opportunities to practise and develop your analytical and communication skills.

The aim of this subject is to give participants both practical experience in, and theoretical insights into, elements of engineering innovation.

The subject is intense, challenging, experiential and requires significant self-direction. Participants will work on an innovation project sponsored by a local organisation.

A key theme is that the individual cannot be separated from the technical processes of engineering innovation. The impact of both individual and team contributions to the engineering and innovation processes will be examined in the context of real world challenges.

Creating Innovative Engineering (CIE) and its companion subject, Creating Innovative Professionals ENGR90039 (CIP), are delivered by the University's Innovation Practice Program. To learn more about the Program, including the range of organizations that have participated as sponsors, examples of past projects and to hear students talk about their experiences in taking CIE/CIP, please go to the Innovation Practice Program’s website.

All project sponsors will require that students maintain the confidentiality of their proprietary information. Some project sponsors will require students to assign any Intellectual Property created (other than Copyright in their Assessment Materials) to the University. The projects may vary in the hours needed for a successful outcome.

This subject aims to give participants theoretical frameworks, practical insights, and preliminary skills to work in their chosen profession in contexts where determining what problem to work on is an important complement to knowing how to solve that problem.

Participants will develop these understandings, insights and skills by working in teams on a strategically-important innovation challenge sponsored by an industry organisation. This subject is similar to Creating Innovative Engineering (ENGR90034), but is designed for students seeking a multi-disciplinary learning experience.

Participants will learn theories of human-centred innovation and apply them in their project. They will learn how to work in teams and use those skills to deliver the project. They will learn to conceptualise their career as an innovation project, and how to apply the innovation skills and theories presented in the subject to their own careers.

The subject is challenging, experiential and requires significant self-direction.

Creating Innovative Professionals (CIP) and its companion subject, Creating Innovative Engineering ENGR90034 (CIE), are delivered by the University's Innovation Practice Program. To learn more about the Program, including the range of organizations that have participated as sponsors, examples of past projects and to hear students talk about their experiences in taking CIE/CIP, please go to the Innovation Practice Program’s website.

All project sponsors will require students to maintain the confidentiality of their proprietary information. The University will require all students (except those working on projects sponsored by the University itself) to assign any Intellectual Property they create (other than Copyright in their Assessment Materials) to the sponsor of their project.

This subject is designed for students with no prior knowledge of biology. The subject will focus on establishing foundational knowledge in biology and building on this to provide students with a thorough understanding of key concepts. It explores the diversity and unity of life through the lens of five core concepts: evolution, cell theory, regulation, transmission of information and interconnectedness in biological systems. These concepts will be studied at the molecular, cellular, and individual level, including the evolution of life from the abiotic to the individual, the molecular and physical structure of the cell, cell replication and gene expression, homeostasis, photosynthesis and respiration, and interactions within and between organisms.

This subject builds on students’ prior knowledge of biology, exploring the diversity and unity of life through the lens of five core concepts: evolution, cell theory, regulation, transmission of information and interconnectedness in biological systems. These concepts will be studied at the molecular, cellular, and individual level, including the evolution of life from the abiotic to the individual, the molecular and physical structure of the cell, cell replication and gene expression, homeostasis, photosynthesis and respiration, and interactions within and between organisms.

This subject provides an introduction to the basic concepts of General Chemistry, including the periodic table, elements, atoms, and states of matter; gases; elementary quantum mechanics, atomic spectra and atomic structure; structure and bonding in elements and compounds of groups 14-18; the chemistry of carbon-based compounds, including structure and bonding of alkanes, alkenes and alkynes, chirality, nomenclature, benzene and its derivatives, functional groups; intermolecular forces; energy and thermochemistry; chemical equilibrium; acid-base chemistry including the strength of acids and bases; physical properties of solutions; solutions and pH equilibria.

This subject introduces important mathematical methods required in engineering such as manipulating vector differential operators, computing multiple integrals and using integral theorems. A range of ordinary and partial differential equations are solved by a variety of methods and their solution behaviour is interpreted. The subject also introduces sequences and series including the concepts of convergence and divergence.

Topics include: Vector calculus, including Gauss’ and Stokes’ Theorems; sequences and series; Fourier series, Laplace transforms; systems of homogeneous ordinary differential equations, including phase plane and linearization for nonlinear systems; second order partial differential equations and separation of variables.

Mechanical forces play a critical role in the healthy function of the human body, from movement during walking to beating of the heart. Mechanical forces also affect the properties and function of engineered tissues and influence the migration and spread of cancer cells through the body. This subject introduces students to fundamental principles in mechanics including analysis of bioengineering systems under static equilibrium conditions, analysis of forces during dynamic motion, mechanical behaviour and strength of biomaterials. Topics covered in this subject will include: Newtons’ laws of motion; stress and strain analysis in mechanical and biological systems subjected to different types of static loads; fundamentals of mechanical testing and failure analysis for biomaterials characterisation; fundamental physics underpinning motion of rigid bodies. Topics will draw on real-world bioengineering applications.

This subject teaches the fundamental theory, design and operational principles of biomedical instrumentation and measurement systems for the design of electronics for measurement and analysis of physiological parameters of the body and organs. The subject provides theory and practical exposure to understanding the basis of physiological signals and analysing biomedical signals, including hands-on experience in designing and building bioinstrumentation systems that can measure biological signals. Students will be introduced to medical devices, design principles, biomedical signals, biomedical instrumentation circuits, mobile health technology, wearables, and electrical safety and systems. These topics will be complemented by exposure to software tools for electronic circuit simulation and design.

This subject teaches the fundamentals of signal processing in a biomedical engineering context. Students will be introduced to digital sampling of analog signals, frequency domain analysis, design of digital filters, parameter estimation techniques and Wiener and Kalman filtering. The subject includes analysis and design for biomedical engineering applications.

This subject will cover the physics of fluids, with a special focus on biologically relevant fluid flows. This includes the flow of bodily fluids in biomedical testing devices and in therapeutic systems. Students will study fundamental fluids mechanics principles and develop an understanding of the mathematics that describe them. These principles will then be employed using computational approaches in real-world applications for fluid mechanics, including pipe flow, microfluidics, pumps and rheology.

This subject teaches fundamentals of data analysis as relevant to modern biomedical engineering, in an integrated approach that combines theory with highly contextualised, project-based learning. Students are introduced to the foundations of probability and random variables, statistical hypothesis testing, linear and nonlinear regression, data classification and dimensionality reduction techniques. Each topic is explicated via case studies from clinical, industrial and research applications of biomedical engineering, covering topics in biomechanics, biosensors, bioinformatics, biomedical imaging and biomaterials.

Biomechanics, which relates structure and function in biological systems, is important in the understanding of human movement, and in the treatment of conditions affecting the musculoskeletal and neuromuscular systems. This subject introduces students to musculoskeletal biomechanics of the human body, with applications to the behaviour of biological tissues such as bone, cartilage, ligament and muscle during human movement.

The subject will provide theory and practical exposure to human motion measurement and modelling of the joint forces and moments that actuate human movement. This subject will introduce biomechanics in sport, including performance, injury and injury prevention. Ageing and associated musculoskeletal disorders will also be included, as well an overview of orthopaedics strategies for the treatment of end-stage bone and joint conditions, including joint replacements and surgical reconstruction.

This subject will cover key aspects of engineering management to help students prepare for working in the biomedical engineering industry including the processes and regulations of therapeutic goods.

It will focus on Biomedical Engineering Management, including the engineer and professional practice, the functions of professional societies; systems engineering and management processes of planning, organisation, leadership and control of human, physical and financial resources, biomedical engineering and quality management systems including ISO 9000 series requirements. This subject will also cover regulations, including risk management and international and Australian regulatory guidelines focusing on medical device regulations, classifications and standards. Also taught in this subject will be human clinical trials, regulation and ethics, design and evaluation of human clinical trials, requirements for post market monitoring, and medical device registries.

AIMS

This subject introduces students to the basic mechanisms of information processing and learning in the brain and nervous system. The subject builds upon signals and systems modelling approaches to demonstrate the application of mathematical and computation modelling to understanding and simulating neural systems. Aspects of neural modelling that are introduced include: membrane potential, action potentials, neural coding, neural models and neural learning. The application of neural information processing is demonstrated in areas such as: electrophysiology, and neuroprostheses. Material is reinforced through MATLAB and/or NEURON based laboratories.

INDICATIVE CONTENT

Topics include:

Neural information processing analysed using information theoretic measures; generation and propagation of action potentials (spikes); Hodgkin-Huxley equations; coding and transmission of neural information (spiking rate, correlation and synchronisation); neural models (binary, rate based, integrate & fire, Hodgkin-Huxley, and multicompartmental); synaptic plasticity and learning in biological neural systems (synaptic basis of learning, short term, medium term and long term, and rate based Hebbian learning models); spike-timing dependent plasticity (STDP) of synapses; higher order neural pathways and systems (cortical structure and circuits).

AIMS

Students studying Tissue Engineering and Stem Cells will become familiar with the history, scope and potential of tissue engineering, and the potential role of stem cells in this field. This subject will address the use of biomaterials in tissue engineering; major scaffold materials and fabrication methods, scaffold strength and degradation; cell sources, selection, challenges and potential manipulation; cell-surface interactions, biocompatibility and the foreign body reaction; the role and delivery of growth factors for tissue engineering applications; in vitro and in vivo tissue engineering strategies, challenges, cell culture, scale-up issues and transport modelling; ethical and regulatory issues; clinical applications of tissue engineering, such as bone regeneration, breast reconstruction, cardiac and corneal tissue engineering, and organogenesis (e.g. pancreas).

This subject provides students with exposure to and understanding of a range of new and emerging applications of biomedical engineering. It includes research-led learning with opportunities to interact with experts and active researchers in the fields of stem cells and tissue engineering. The subject covers aspects of biology, materials engineering and process engineering which underpin tissue engineering and provides examples of the applications of this evolving area of technology.

INDICATIVE CONTENT

Topics covered include tissue organization & tissue dynamics, stem cells, cellular fate processes & signalling, the ECM as scaffold material, natural and synthetic polymers for tissue engineering, bioceramics, scaffold design and fabrication, tailoring biomaterials, cell culture and cell nutrition, bioreactors for tissue engineering, risk management in tissue engineering, ethics in tissue engineering.

AIMS

This subject introduces students to the engineering, physics and physiology of medical imaging, including the history and progression of medical imaging modalities as well as emerging imaging technologies in clinical and research practise. Topics covered include: x-ray, computed tomography, positron emission tomography, magnetic resonance imaging and ultrasound.

INDICATIVE CONTENT

Topics include:

Image metrics including signal-to-noise and contrast-to-noise ratios, image resolution, image operations including convolution, filtering and edge detection;

Biophysical principles of X-ray, CT, PET, SPECT, MRI and ultrasound, and the mathematics of image reconstruction for each modality, including filtered backprojection and fourier reconstruction methods;

This material is complemented by the use of software tools (e.g. MATLAB) for data simulation, modelling, image manipulation and reconstruction techniques.

AIMS and INDICATIVE CONTENT

In this subject students should gain an understanding of the structure and function of the skeletal, muscular, and sensory systems of the human body.

Students should also be able to formulate simple, integrative models of the human neuromusculoskeletal system; and to use computational models of the human body to analyse muscle function during activities like standing, walking, running and jumping.

AIMS:

This subject introduces mathematical and computational modelling, simulation and analysis of biological systems. The emphasis is on developing models, with examples, using MATLAB.

INDICATIVE CONTENT:

Topics include:

Modelling biochemical reactions. Law of mass action. Enzymes and regulation of enzyme reactions. Thermodynamics of reversible biochemical reactions. Cellular homeostasis. Application of ordinary differential equations to these problems.

Modelling large reaction networks. Flux balance analysis and constraint-based methods. Genome-scale models. Regulation of gene expression. Gene regulatory networks in systems and synthetic biology. Network inference and statistical modelling of –omic data. Knowledge-based modelling in systems biology.

AIMS

Technological advances in obtaining high throughput data have stimulated the development of new computational approaches to bioinformatics. This subject will cover core computational challenges in analysing bioinformatics data. We cover important algorithmic approaches and data structures used in solving these problems, and the challenges that arise as these problems increase in scale.

The subject is a core subject in the MSc (Bioinformatics) and is an elective in the Master of Information Technology and the Master of Engineering. It can also be taken by PhD students and by undergraduate students, subject to the approval of the lecturer.

INDICATIVE CONTENT

The subject covers key algorithms used in bioinformatics, with a focus on genomics. Indicative topics are: sequence alignment (dynamic algorithms and seed-and-extend), genome assembly, variant detection, phylogenetic reconstruction, genomic intervals, complexity and correctness of algorithms, clustering and classification of genomics data, data reduction and visualisation.
The subject assumes you have experience in programming and familiarity with the foundations of genomics.

AIM

The study of genomics is on the forefront of biology. Current laboratory technologies generate huge amounts of data. Computational analysis is necessary to make sense of these data. This subject covers a broad range of approaches to the computational analysis of genomic data. Students learn the theory behind the different approaches to genomic analysis, preparing them to use existing methods appropriately and positioning them to develop new ways to analyse genomic data.

The subject is a core subject in the MSc (Bioinformatics), and is an elective in the Master of Information Technology and the Master of Engineering. It can also be taken by PhD students and by undergraduate students, subject to the approval of the lecturer.

INDICATIVE CONTENT

This subject covers computational analysis of genomic data, from the perspective of information theory. Topics include information theoretic analysis of genomic sequences; sequence comparison, including heuristic approaches and multiple sequence alignment; and approaches to motif finding and genome annotation, including probabilistic modelling and visualization, computational detection of RNA families, and current challenges in protein structure determination. Practical work includes writing bioinformatics applications programs and preparing a research report that uses existing bioinformatics web resources.

AIMS

This subject involves undertaking a major research or advanced innovative design project requiring an independent investigation and the preparation of reports on an approved topic. Students will present their findings in a conference presentation format, held at the end of the project cycle in the latter half of semester two.

The emphasis of the project can be associated with either:

• Explorative approach, where students will pursue outcomes associated with new knowledge or understanding within the biomedical engineering or science disciplines, often as an adjunct to existing academic research initiatives.
• A well-defined innovative project, usually based on a research and development required by an external industrial client. Students will be tutored in the synthesis of practical solutions to complex technical problems within a structured working environment, as if they were research and development professional engineers.

This subject has been integrated with the Skills Towards Employment Program (STEP) and contains activities that can assist in the completion of the Engineering Practice Hurdle (EPH).

AIMS

This subject involves undertaking a major research or advanced innovative design project requiring an independent investigation and the preparation of reports on an approved topic. Students will present their findings in a conference presentation format, held at the end of the project cycle in the latter half of semester two. The emphasis of the project can be associated with either:

Explorative approach, where students will pursue outcomes associated with new knowledge or understanding within the biomedical engineering or science disciplines, often as an adjunct to existing academic research initiatives.

A well-defined innovative project, usually based on a research and development required by an external industrial client. Students will be tutored in the synthesis of practical solutions to complex technical problems within a structured working environment, as if they were research and development professional engineers.

INDICATIVE CONTENT

Topics include: Technical report writing, engineering design planning and conducting experiments and test, data acquisition and analysis, public speaking, project presentation skills.

This subject has been integrated with the Skills Towards Employment Program (STEP) and contains activities that can assist in the completion of the Engineering Practice Hurdle (EPH).

Note: Enrolment in BMEN90031 Biomedical Engineering Capstone Project Part 1 is subject to approval from the subject coordinator. Students commence BMEN90031 Biomedical Engineering Capstone Project Part 1 in Semester 2 and then subsequently continue BMEN90032 Biomedical Engineering Capstone Project Part 2 in Semester 1 in the following year. Upon successful completion of this project, students will receive 25 points credit.

Refer to BMEN90031 Biomedical Engineering Capstone Project Part 1 for details.

AIMS

BioDesign Innovation is a “real world” course in creating successful medical devices. The course is given over two semesters of one academic year and is composed of frontal lectures, practical training, and a guided project. The first semester focusses on identifying clinical needs, brainstorming and concept creation. The second semester focusses on concept development and business implementation. Teams of 2-3 students from engineering disciplines will team up with business students and with people from medical and law backgrounds to conceive and design an innovative medical device, taking it through all steps of development. The students in the teams will complete assessment items together, each member primarily contributing according to their specialisation. The teams will create an engineering prototype of their invention, draft a provisional patent application, and compose a detailed business plan. BioDesign Innovation is taught by a combination of academics, medical device entrepreneurs, corporate executives, intellectual property attorneys and venture capitalists. As such, it provides a unique opportunity to gain real world experience while still in an academic environment.

AIMS

While many chemical engineers work in process engineering, the interdisciplinary nature of chemical engineering is applicable to product development and design where between 30 % to 50% of chemical engineers work in product development depending on the country. The types of products can be quite diverse in nature, ranging from sunscreens, shampoo, pharmaceuticals or mass-produced ice-cream to more device-oriented products such as energy storage devices (e.g., super-capacitors, graphene based materials), drug delivery materials (e.g. polymer particles, capsules or hydrogels), tissue engineered materials or even kidney dialysis units. In practice, chemical engineers work with other engineers (e.g., materials, biomedical, mechanical) in product design in a range of industrial sectors including foods, cosmetics, personal care products, pharmaceuticals, ceramics, 2D materials, veterinary and agricultural sciences, minerals purification, biochemical processing and biomedical engineering.

This subject allows students to better understand product design by learning about the unifying fundamental structure-function relationships and material properties found in these complex products. Students will learn how to use >a basic knowledge of interfacial phenomena to see how products or devices are designed, manufactured and analysed. In addition, students will be introduced to the key stages of product development, the importance of the needs and specifications of the target users and customers and decision gating processes involved in getting a product from an idea to market. Students will also learn about some of the instruments used in industry for analysis of products, from the basics to state-of-the-art. Students will be able to use the information from the lectures and tutorials to focus on an area of interest to explore how a product or device was discovered, developed, designed delivered for a set of users or customers. They will also be able to present this information to a broader audience.

INDICATIVE CONTENT

Fundamental topics covered in the subject include: how colloidal particle diffusion mediates particle suspension stability and shelf life, how to link interparticle forces to stability, shelf life and particle suspension flow, i.e., viscoelasticity and rheology; the formation and properties of emulsions and foams, the behaviour of polymers in solution and how this affects polymer adsorption to surfaces and coating formation; the viscoelastic behaviour of polymer solutions and how polymers are used in soft materials including polymer coatings, gels and hydrogels; the formation solution microstructure through the self-assembly of amphiphilic molecules to form micelles, vesicles and hexagonal phases. The common characterisation and analytical methods used to study these phenomena including a number of more advanced methods in spectroscopy, microscopy, particle size measurement and image analysis.

AIMS

This subject aims to provide an advanced understanding of pharmaceutical and biochemical production processes; students will learn about processes in Australia and the Asia-Pacific region.

INDICATIVE CONTENT

How are drugs made? What steps are required to progress a successful drug candidate from the laboratory to large scale manufacture? How can cells and enzymes be used in manufacturing? This subject will answer these questions, examining unit operations and the design and operation of manufacturing processes that are used to make a range of products including opiates, blood plasma products, vaccines, monoclonal antibodies and other medicines. Unit operations will include the growth of bacterial, animal, plant and fungal cells, cell disruption and methods for product separation and purification, such as chromatography. Case studies will include the production of recombinant proteins and amino acids and the genetic techniques required to make these products. The sustainable production of other biochemicals will also be discussed, including biofuels and the growth of algae. Students will learn how cellular processes can also be used by chemical engineers to improve process efficiencies, clean up our environment and reduce chemical waste. Regulation, Good Manufacturing Practice and Validation processes will be introduced, along with the design of laboratories, pilot plants and manufacturing facilities and associated utilities and services. Industry speakers will also highlight new opportunities and best practice within the Australian pharmaceutical industry. Students will also be introduced to relevant analytical techniques used to track production and purity and will become familiar with the research literature in this field.

AIMS

The subject will introduce the basics of computer networks to students through a study of layered models of computer networks and applications. The first half of the subject deals with data communication protocols in the lower layers of OSI and TCP/IP reference models. The students will be exposed to the working of various fundamental networking technologies such as wireless, LAN, RFID and sensor networks. The second half of the subject deals with the upper layers of the TCP/IP reference model through a study of several Internet applications.

INDICATIVE CONTENT

Topics covered include: Introduction to Internet, OSI reference model layers, protocols and services, data transmission basics, interface standards, network topologies, data link protocols, message routing, LANs, WANs, TCP/IP suite, detailed study of common network applications (e.g., email, news, FTP, Web), network management, and current and future developments in network hardware and protocols.

AIMS

The aim of this subject is for students to develop familiarity and competence in assessing and designing computer programs for computational efficiency. Although computers manipulate data very quickly, to solve large-scale problems, we must design strategies so that the calculations combine effectively. Over the latter half of the 20th century, an elegant theory of computational efficiency developed. This subject introduces students to the fundamentals of this theory and to many of the classical algorithms and data structures that solve key computational questions. These questions include distance computations in networks, searching items in large collections, and sorting them in order.

INDICATIVE CONTENT

Topics covered include complexity classes and asymptotic notation; empirical analysis of algorithms; abstract data types including queues, trees, priority queues and graphs; algorithmic techniques including brute force, divide-and-conquer, dynamic programming and greedy approaches; space and time trade-offs; and the theoretical limits of algorithm power.

AIMS

The aims for this subject is for students to develop an understanding of approaches to solving moderately complex problems with computers, and to be able to demonstrate proficiency in designing and writing programs. The programming language used is Java.

INDICATIVE CONTENT

Topics covered will include:

• Java basics
• Console input/output
• Control flow
• Defining classes
• Using object references
• Programming with arrays
• Inheritance
• Polymorphism and abstract classes
• Exception handling
• UML basics
• Interfaces
• Generics

AIMS

This subject provides an introduction to probability theory, random variables, random vectors, decision tests, and stochastic processes. Uncertainty is inevitable in real engineering systems, and the laws of probability offer a powerful way to evaluate uncertainty, to predict and to make decisions according to well-defined, quantitative principles. The material covered is important in fields such as communications, data networks, signal processing and electronics. This subject is a core requirement in the Master of Engineering (Electrical, Mechanical and Mechatronics).

INDICATIVE CONTENT

Topics include:

• Foundations – combinatorial analysis, axioms of probability, independence, conditional probability, Bayes’ rule;
• Random variables (rv’s)– definition; cumulative distribution, probability mass and probability density functions; expectation and variance; functions of an rv; important distributions and their properties and uses;
• Multiple random variables – joint cumulative distribution, probability mass and probability density functions; independent rv’s; correlation and covariance; conditional distributions and expectation; functions of several rv’s; jointly Gaussian rv’s; random vectors;
• Sums, inequalities and limit theorems – sums of rv’s, moment generating function; Markov and Chebychev inequalities; weak and strong laws of large numbers; the Central Limit Theorem;
• Decision testing - maximum likelihood, maximum a posterior, minimum cost and Neyman-Pearson rules; basic minimum mean-square error estimation;
• Stochastic processes – mean and autocorrelation functions, strict and wide-sense stationarity; ergodicity; important processes and their properties and uses;
• Introduction to Markov chains.

This material is complemented by exposure to examples from electrical engineering and software tools (e.g. MATLAB) for computation and simulations.

AIMS

This subject provides an introduction to automatic control systems, with an emphasis on classical techniques for the analysis and design of feedback interconnections. The main challenge in automatic control is to achieve desired performance in the presence of uncertainty about the system dynamics and the operating environment. Feedback control is one way to deal with modelling uncertainty in the design of engineering systems. This subject is a core requirement in the Master of Engineering (Electrical, Electrical with Business, Mechanical, Mechanical with Business and Mechatronics).

INDICATIVE CONTENT

Topics include:

* Modelling for control, linearization, relationships between time and frequency domain models of linear time-invariant dynamical systems, and the structure, stability, performance, and robustness of feedback interconnections;

* Frequency-domain analysis and design, Nyquist and Bode plots, gain and phase margins, loop-shaping with proportional, integral, lead, and lag compensators, loop delays, and fundamental limitations in design; and

* Actuator constraints and anti-windup compensation.

This material is complemented by the use of software tools (e.g. MATLAB/Simulink) for computation and simulation, and exposure to control system hardware in the laboratory.

AIMS

This subject provides an introduction to the fundamental theory of time domain and frequency domain representation of discrete time signals and linear time invariant dynamical systems, and how this theory is used to analyse and design digital signal processing systems and algorithms. Topics include:

• Applications of signal processing techniques;
• Sampling of analog signals, anti-aliasing filters;
• Frequency-domain analysis of signals and systems, Discrete Time Fourier Transform, Discrete Fourier Transform, Fast Fourier Transform;
• Digital filters, low-pass, high-pass, band-pass, stop-band and all pass filters. Phase and group delay, FIR and IIR filters;
• Design of digital FIR and IIR filters;
• Multi-rate signal processing, with a focus on up-sampling, down-sampling, and sampling rate conversion;
• Simple non-parametric methods for spectral estimation.

This fundamental material will be complemented by exposure to MATLAB tools for signal analysis and a DSP (Digital Signal Processor) based development platform for the implementation of signal processing algorithms in the laboratory.

INDICATIVE CONTENT

Sampling of continuous time signals, Design of anti-aliasing filters, Time and frequency representation of discrete time signals and discrete time linear time invariant systems, Discrete Time Fourier Transform and z-transform and their properties, Low order lowpass, highpass, bandpass, bandstop filters, All-pass filter, Design of IIR filters using the bilinear transformation, Design of FIR filters with linear phase using windowing techniques and the Parks McClelland method, Discrete Time Fourier transform and its properties, Fast Fourier Transform, The use of the DFT in implementation of linear filtering algorithms, Up-sampling and down-sampling, multistage and computationally efficient implementations of up-samplers and down-samplers, Energy and power spectra for deterministic signals.

AIM

Within this subject you will learn how to use Computational Fluid Dynamics (CFD) to solve practical industrial and research related fluid flow and heat/mass transfer problems. The major assessment within this subject is a capstone project, requiring a CFD treatment of a major piece of equipment related to your degree discipline area. This project may be industry or research based. Learning is supported by a number of structured group-based workshops completed throughout the semester, requiring completion of associated on-line quizzes. This subject may be completed entirely online. Guest lectures from academia and industry will share insights into how they use CFD in their research/workplace.

The content of this subject is split between two related modules:

1) Fundamentals of CFD: Within this module we will cover the mathematical basis of modern CFD methods, using MATLAB as a programming tool to demonstrate specific fundamental concepts. Specific topics include overview, conservation laws, advection-diffusion equations, differencing schemes, finite volume method, stability analysis, error analysis, boundary conditions and solution algorithms for solving Navier-Stokes equations.

2) Applications of CFD: This module will be based around the industry-relevant CFD package ANSYS Fluent. Specific topics include: How to run a basic simulation, meshing, laminar 2D and 3D flows, boundary conditions, discretisation methods, visualisation, turbulence, disperse multiphase flows, free-surface multiphase flows, coupled heat and mass transfer, chemical reactions, use of CFD in industry and research.

AIMS

This subject involves students undertaking professional work experience at a Host Organisation’s premises. Students will work under the supervision of both a member of academic staff and an external supervisor at the Host Organisation.

During the period of work experience, students will be introduced to workplace culture and be offered the opportunity to strengthen their employability. Students will undertake seminars covering topics that will include professional standards of behaviour and ethical conduct, working in teams, time management and workplace networking.

This subject is designed to provide students with detailed training in statistical methods as applied to the design and analysis of projects undertaken by postgraduate students, across all disciplines.

AIMS

There are 2 related, major topics of study in this subject. Each of these topics will analyse aspects of important thermodynamic devices and will then be integrated to analyse their combined effects in selected devices:

• Cycle analysis: gas turbines, refrigeration and steam cycles
• Heat transfer: conduction, convection, radiation and heat exchangers

INDICATIVE CONTENT

• Heat transfer: 1-D conduction, external convection, internal convection, heat exchangers and thermal radiation
• Cycle analysis: Brayton cycles, turboject cycles, Rankine cycles, refrigeration cycles

Successful commercialisation of scientific discoveries and new technologies occurs in a unique business environment where scientific and business interests and personalities must productively interact.

The subject will develop a critical understanding of the context in which the commercialisation of science occurs, and the opportunities and challenges encountered. Topics covered within the subject will include the nature and types of intellectual property, how it can be protected, valued, managed and strengthened, its use as a commercial tool, exploration of the barriers to commercialisation, what strategies can be used to exploit IP, how to develop a commercial plan and leverage finance for the commercialisation of IP.

What does it take to develop something innovative and then move it from the laboratory out into the real world? Scientists must negotiate a labyrinth of hurdles, ranging from conducting bullet-proof data analysis, designing clinical trials, developing and managing intellectual property, assessing contracts, and setting up Total Quality Management systems in a biotech setting. Students will learn how to navigate these hurdles as applied to a range of possible inventions, such as therapeutics, diagnostics, medical devices, GMOs and other bio-science-related creations.

Projects drive most modern science organisations. Learn how to plan and manage projects, and to relate to a client, team members, and to other stakeholders. The subject covers the processes and tools / techniques in project management as well as the ‘soft side’ of managing people in projects. The subject uses the project management body of knowledge (PMBOK) covering the competencies in project management including scope, time, cost, quality, resource, risk, communication and integration management.

AIMS

This subject introduces students to the basic mechanisms of information processing and learning in the brain and nervous system. The subject builds upon signals and systems modelling approaches to demonstrate the application of mathematical and computation modelling to understanding and simulating neural systems. Aspects of neural modelling that are introduced include: membrane potential, action potentials, neural coding, neural models and neural learning. The application of neural information processing is demonstrated in areas such as: electrophysiology, and neuroprostheses. Material is reinforced through MATLAB and/or NEURON based laboratories.

INDICATIVE CONTENT

Topics include:

Neural information processing analysed using information theoretic measures; generation and propagation of action potentials (spikes); Hodgkin-Huxley equations; coding and transmission of neural information (spiking rate, correlation and synchronisation); neural models (binary, rate based, integrate & fire, Hodgkin-Huxley, and multicompartmental); synaptic plasticity and learning in biological neural systems (synaptic basis of learning, short term, medium term and long term, and rate based Hebbian learning models); spike-timing dependent plasticity (STDP) of synapses; higher order neural pathways and systems (cortical structure and circuits).

AIMS

Students studying Tissue Engineering and Stem Cells will become familiar with the history, scope and potential of tissue engineering, and the potential role of stem cells in this field. This subject will address the use of biomaterials in tissue engineering; major scaffold materials and fabrication methods, scaffold strength and degradation; cell sources, selection, challenges and potential manipulation; cell-surface interactions, biocompatibility and the foreign body reaction; the role and delivery of growth factors for tissue engineering applications; in vitro and in vivo tissue engineering strategies, challenges, cell culture, scale-up issues and transport modelling; ethical and regulatory issues; clinical applications of tissue engineering, such as bone regeneration, breast reconstruction, cardiac and corneal tissue engineering, and organogenesis (e.g. pancreas).

This subject provides students with exposure to and understanding of a range of new and emerging applications of biomedical engineering. It includes research-led learning with opportunities to interact with experts and active researchers in the fields of stem cells and tissue engineering. The subject covers aspects of biology, materials engineering and process engineering which underpin tissue engineering and provides examples of the applications of this evolving area of technology.

INDICATIVE CONTENT

Topics covered include tissue organization & tissue dynamics, stem cells, cellular fate processes & signalling, the ECM as scaffold material, natural and synthetic polymers for tissue engineering, bioceramics, scaffold design and fabrication, tailoring biomaterials, cell culture and cell nutrition, bioreactors for tissue engineering, risk management in tissue engineering, ethics in tissue engineering.

AIMS

This subject introduces students to the engineering, physics and physiology of medical imaging, including the history and progression of medical imaging modalities as well as emerging imaging technologies in clinical and research practise. Topics covered include: x-ray, computed tomography, positron emission tomography, magnetic resonance imaging and ultrasound.

INDICATIVE CONTENT

Topics include:

Image metrics including signal-to-noise and contrast-to-noise ratios, image resolution, image operations including convolution, filtering and edge detection;

Biophysical principles of X-ray, CT, PET, SPECT, MRI and ultrasound, and the mathematics of image reconstruction for each modality, including filtered backprojection and fourier reconstruction methods;

This material is complemented by the use of software tools (e.g. MATLAB) for data simulation, modelling, image manipulation and reconstruction techniques.

AIMS and INDICATIVE CONTENT

In this subject students should gain an understanding of the structure and function of the skeletal, muscular, and sensory systems of the human body.

Students should also be able to formulate simple, integrative models of the human neuromusculoskeletal system; and to use computational models of the human body to analyse muscle function during activities like standing, walking, running and jumping.

AIMS:

This subject introduces mathematical and computational modelling, simulation and analysis of biological systems. The emphasis is on developing models, with examples, using MATLAB.

INDICATIVE CONTENT:

Topics include:

Modelling biochemical reactions. Law of mass action. Enzymes and regulation of enzyme reactions. Thermodynamics of reversible biochemical reactions. Cellular homeostasis. Application of ordinary differential equations to these problems.

Modelling large reaction networks. Flux balance analysis and constraint-based methods. Genome-scale models. Regulation of gene expression. Gene regulatory networks in systems and synthetic biology. Network inference and statistical modelling of –omic data. Knowledge-based modelling in systems biology.

AIMS

Technological advances in obtaining high throughput data have stimulated the development of new computational approaches to bioinformatics. This subject will cover core computational challenges in analysing bioinformatics data. We cover important algorithmic approaches and data structures used in solving these problems, and the challenges that arise as these problems increase in scale.

The subject is a core subject in the MSc (Bioinformatics) and is an elective in the Master of Information Technology and the Master of Engineering. It can also be taken by PhD students and by undergraduate students, subject to the approval of the lecturer.

INDICATIVE CONTENT

The subject covers key algorithms used in bioinformatics, with a focus on genomics. Indicative topics are: sequence alignment (dynamic algorithms and seed-and-extend), genome assembly, variant detection, phylogenetic reconstruction, genomic intervals, complexity and correctness of algorithms, clustering and classification of genomics data, data reduction and visualisation.
The subject assumes you have experience in programming and familiarity with the foundations of genomics.

AIM

The study of genomics is on the forefront of biology. Current laboratory technologies generate huge amounts of data. Computational analysis is necessary to make sense of these data. This subject covers a broad range of approaches to the computational analysis of genomic data. Students learn the theory behind the different approaches to genomic analysis, preparing them to use existing methods appropriately and positioning them to develop new ways to analyse genomic data.

The subject is a core subject in the MSc (Bioinformatics), and is an elective in the Master of Information Technology and the Master of Engineering. It can also be taken by PhD students and by undergraduate students, subject to the approval of the lecturer.

INDICATIVE CONTENT

This subject covers computational analysis of genomic data, from the perspective of information theory. Topics include information theoretic analysis of genomic sequences; sequence comparison, including heuristic approaches and multiple sequence alignment; and approaches to motif finding and genome annotation, including probabilistic modelling and visualization, computational detection of RNA families, and current challenges in protein structure determination. Practical work includes writing bioinformatics applications programs and preparing a research report that uses existing bioinformatics web resources.