Advances in digital technology are creating new ways to quantify biological processes and properties, from the scale of molecules to ecosystems. The life scientist of the 21st century needs to understand how to collect, manage, synthesise, and communicate this information within a reproducible workflow in order to make robust inferences about the natural world. This intensive unit of study will introduce you to key concepts and tools across three modules: digital project and data management, evidence synthesis and meta-analysis, and scientific coding using R. The focus is on active learning, discussion, and problem-solving across intensive workshop-based practicals, rather than the traditional lecture format. By completing this unit you will further understand the practical realities of scientific inquiry. To that end, you will develop a flexible skillet for conducting reproducible and open research to ensure the results of your work are maximally beneficial to both your future self and the broader community. Knowledge of how to work with data through the entire pipeline -from sampling to synthesis-will be useful wherever it is encountered in your education, career, and life.

An indispensable attribute of an effective scientific researcher is the ability to collect, analyse and interpret data. Central to this process is the ability to create hypotheses and test these by using rigorous experimental designs. This modular unit of study will introduce the key concepts of experimental design and data analysis. Specifically, you will learn to formulate experimental aims to test a specific hypothesis. You will develop the skills and understanding required to design a rigorous scientific experiment, including an understanding of concepts such as controls, replicates, sample size, dependent and independent variables and good research practice (e.g. blinding, randomisation). By completing this unit you will develop the knowledge and skills required to appropriately analyse and interpret data in order to draw conclusions in the context of an advanced research project. From this unit of study, you will emerge with a comprehensive understanding of how to optimise the design and analysis of an experiment to most effectively answer scientific questions.

This unit of study is aimed at developing advanced skills in spatial predictive modelling including mapping of environmental properties and image classification. The units begins with an introductory module on key concepts in GIS, and the use of the R ecosystem for spatial science. In this module you will learn how to process spatial data in a reproducible manner and get it into a format ready for spatial modelling. In the second module we will cover spatial modelling approaches including geostatistics, statistical and machine learning models. Finally, in the third module you will have an opportunity to apply your knowledge in a spatial modelling project of your choice.

Living organisms are impacted by processes that occur across a very wide range of scales. These range from rapid processes at the molecular and cellular scale to multi-year processes at environmental and evolutionary scales. One of the great challenges for modern systems biology is integrating measurements across these scales to understand gene x environment interactions. This unit will develop your skills in this area through critical analysis of a series of recent research papers on a themed topic in small group discussions. For each paper we will explore principles behind the key methods and the methods' practicality. We will look at how those methods were incorporated into an experimental design to address a biological question. We will critically assess the support for conclusions in their paper and their scientific significance. By doing this unit you will develop skills in reading and interpreting primary scientific literature and an advanced understanding of the modern topic in systems biology. You will gain a high level of understanding of the theory of key biochemical and statistical methods for analysis of genes, proteins, and cells in biological systems. You will gain the confidence to apply these insights to planning, conducting and reporting your own research findings.

Sophisticated mathematics and numerical programming underlie many computer applications, including weather forecasting, computer security, video games, and computer aided design. This unit of study provides a strong foundational introduction to modern interactive programming, computational algorithms, and numerical analysis. Topics covered include: (I) basics ingredients of programming languages such as syntax, data structures, control structures, memory management and visualisation; (II) basic algorithmic concepts including binary and decimal representations, iteration, linear operations, sources of error, divide-and-concur, algorithmic complexity; and (III) basic numerical schemes for rootfinding, integration/differentiation, differential equations, fast Fourier transforms, Monte Carlo methods, data fitting, discrete and continuous optimisation. You will also learn about the philosophical underpinning of computational mathematics including the emergence of complex behaviour from simple rules, undecidability, modelling the physical world, and the joys of experimental mathematics. When you complete this unit you will have a clear and comprehensive understanding of the building blocks of modern computational methods and the ability to start combining them together in different ways. Mathematics and computing are like cooking. Fundamentally, all you have is sugar, fat, salt, heat, stirring, chopping. But becoming a good chef requires knowing just how to put things together in creative ways that work. In a previous study, you should have learned to cook. Now you're going to learn how to make something someone else might want to pay for more than one time.

"If you can't explain it simply, you don't understand it well enough". This quote is widely attributed to Albert Einstein, but regardless of its provenance, it suggests that one measure of an expert's knowledge can be found in their ability to translate complex ideas so that they are accessible to anyone. The communication of science to the public is essential for science and society. In order to increase public understanding and appreciation of science, researchers must be able to explain their results, and the wider context of their research, to non-experts. This unit will explore some theoretical foundations of science communications, identify outstanding practitioners and empower students to produce effective science communication in different media. In this unit you will learn the necessary skills and techniques to tell engaging and informative science stories in order to bring complex ideas to life, for non-expert audiences. By undertaking this unit you will develop a greater understanding of the wider context of your honours unit, advance your communication skills and be able to explain your honours research to non-expert audiences such as friends, family or future employers. These transferable skills will equip you for future research - where emphasis is increasingly placed on public communication and/or outreach - or professional pathways - where effective communication of complex ideas is highly valued.

In the contemporary world, a wide variety of ethical concerns impinge upon the practice of scientific research. In this unit, you will learn how to identify potential ethical issues within science, acquire the tools necessary to analyse them, and develop the ability to articulate ethically sound insights about how to resolve them. In the first portion of the unit, you will be familiarised with how significant developments in post-World War II science motivated sustained ethical debate among scientists and in society. In the second portion of the unit, you will select from either a Human Ethics module or an Animal Ethics module and learn the requirements of how to ensure your research complies with appropriate national legislation and codes of conduct. By undertaking this unit, you will develop the ability to conduct scientific research in an ethically justifiable way, place scientific developments and their application in a broader social context, and analyse the social implications and ethical issues that may potentially arise in the course of developing scientific knowledge.

This unit will study basic concepts and methods of time series analysis applicable in many real world problems in numerous fields, including economics, finance, insurance, physics, ecology, chemistry, computer science and engineering. This unit will investigate the basic methods of modelling and analyzing of time series data (i.e. data containing serially dependence structure). This can be achieved through learning standard time series procedures on identification of components, autocorrelations, partial autocorrelations and their sampling properties. After setting up these basics, students will learn the theory of stationary univariate time series models including ARMA, ARIMA and SARIMA and their properties. Then the identification, estimation, diagnostic model checking, decision making and forecasting methods based on these models will be developed with applications. The spectral theory of time series, estimation of spectra using periodogram and consistent estimation of spectra using lag-windows will be studied in detail. Further, the methods of analyzing long memory and time series and heteroscedastic time series models including ARCH, GARCH, ACD, SCD and SV models from financial econometrics and the analysis of vector ARIMA models will be developed with applications. By completing this unit, students will develop the essential basis for further studies, such as financial econometrics and financial time series. The skills gained through this unit of study will form a strong foundation to work in a financial industry or in a related research organization.

In our ever-changing world, we are facing a new data-driven era where the capability to efficiently combine and analyse large data collections is essential for informed decision making in business and government, and for scientific research. Statistics and data analytics consulting provide an important framework for many individuals to seek assistance with statistics and data-driven problems. This unit of study will provide students with an opportunity to gain real-life experience in statistical consulting or work with collaborative (interdisciplinary) research. In this unit, you will have an opportunity to have practical experience in a consultation setting with real clients. You will also apply your statistical knowledge in a diverse collection of consulting projects while learning project and time management skills. In this unit you will need to identify and place the client's problem into an analytical framework, provide a solution within a given time frame and communicate your findings back to the client. All such skills are highly valued by employers. This unit will foster the expertise needed to work in a statistical consulting firm or data analytical team which will be essential for data-driven professional and research pathways in the future.

Applied Statistics fundamentally brings statistical learning to the wider world. Some data sets are complex due to the nature of their responses or predictors or have high dimensionality. These types of data pose theoretical, methodological and computational challenges that require knowledge of advanced modelling techniques, estimation methodologies and model selection skills. In this unit you will investigate contemporary model building, estimation and selection approaches for linear and generalised linear regression models. You will learn about two scenarios in model building: when an extensive search of the model space is possible; and when the dimension is large and either stepwise algorithms or regularisation techniques have to be employed to identify good models. These particular data analysis skills have been foundational in developing modern ideas about science, medicine, economics and society and in the development of new technology and should be in the toolkit of all applied statisticians. This unit will provide you with a strong foundation of critical thinking about statistical modelling and technology and give you the opportunity to engage with applications of these methods across a wide scope of applications and for research or further study.

Independent research can be a life changing experience. In this unit you will complete a research project in the discipline of Quantitative Life Sciences. Together with your supervisor, you will identify a novel research question and develop a hypothesis. You will then design and carry out experiments to test your hypothesis. In terms of assessment, you will communicate the research plan and findings through written tasks and oral presentations culminating in a 20, 000 words honours thesis. Successful completion of your Honours will clearly demonstrate that you have mastered significant research and professional skills for either undertaking a PhD or any variety of future careers.

Independent research can be a life changing experience. In this unit you will complete a research project in the discipline of Quantitative Life Sciences. Together with your supervisor, you will identify a novel research question and develop a hypothesis. You will then design and carry out experiments to test your hypothesis. In terms of assessment, you will communicate the research plan and findings through written tasks and oral presentations culminating in a 20, 000 words honours thesis. Successful completion of your Honours will clearly demonstrate that you have mastered significant research and professional skills for either undertaking a PhD or any variety of future careers.

Independent research can be a life changing experience. In this unit you will complete a research project in the discipline of Quantitative Life Sciences. Together with your supervisor, you will identify a novel research question and develop a hypothesis. You will then design and carry out experiments to test your hypothesis. In terms of assessment, you will communicate the research plan and findings through written tasks and oral presentations culminating in a 20, 000 words honours thesis. Successful completion of your Honours will clearly demonstrate that you have mastered significant research and professional skills for either undertaking a PhD or any variety of future careers.

Independent research can be a life changing experience. In this unit you will complete a research project in the discipline of Quantitative Life Sciences. Together with your supervisor, you will identify a novel research question and develop a hypothesis. You will then design and carry out experiments to test your hypothesis. In terms of assessment, you will communicate the research plan and findings through written tasks and oral presentations culminating in a 20, 000 words honours thesis. Successful completion of your Honours will clearly demonstrate that you have mastered significant research and professional skills for either undertaking a PhD or any variety of future careers.

All students in Science Honours must enrol in this non-assessable unit of study in their final semester. This unit will contain your final Honours mark as calculated from your coursework and research project units.