During their first term in Oxford DTP students undertake an individually tailored selection of the core graduate courses offered by the DTP, which include courses in Programming, Essential Maths and Statistics, Imaging and Image Analysis, Advanced Experimental Techniques, Systems and Synthetic Biology and Scientific Computing. The aim of these foundation modules is to provide an introduction to the quantitative and computational skills that underpin modern scientific research, as well as an awareness of the grand challenges in 21st century bioscience and of the cutting edge experimental techniques and facilities available across the partnership.
Modules are taught in intensive 1-2 week blocks and involve a combination of lectures, individual and team-based problem-solving, project work and hands-on experience. The training offered within the DTP is non-competitive, with a strong emphasis on communication skills and teamwork, and progress is assessed relative to the background and experience of each individual student.
|Introduction to Programming|
The programming module takes students from the very basics of how a computer works and the idea of an operating system, through to file and image processing. By presenting students with two programming languages, over the course of two weeks students will have learned how to select which language is appropriate for the problem in hand and how to tackle that problem.
|Essential Mathematics and Statistics|
Fundamental concepts and methods in mathematics and statistics for students who have little formal training in mathematics.
|Cells, Signalling and Systems
Fundamental concepts in molecular and cellular biology and genetics, and in the structural and functional aspects of biological systems.
|Scientific Computing using Matlab|
Core techniques in scientific programming for applications in biology and biomedicine. Introduces students to the widely used Matlab programming language.
|Introduction to Bioinformatics|
This course provides an introduction to concepts, tools and techniques in bioinformatics and phylogenetics, including sequence databases, sequence alignments, phylogenetics, high-throughput sequencing technologies (both short- and long-read), protein bioinformatics tools, homology modelling, molecular visualisation & setting up and running molecular dynamic simulations.
|Microscopy, Biophysics and Imaging Techniques
Provides an introduction to concepts and techniques in advanced light microscopy and in vivo imaging techniques. The course also introduces a range of current research questions in biological physics, including the underlying physics of the relevant biological systems and the methods that are used and under development for their study.
|Microscopy, Biophysics and Imaging Techniques|
Provides an introduction to concepts and techniques in advanced light microscopy and in vivo imaging techniques.
Fundamental concepts in organic chemistry that are essential for research at the molecular level. Includes a week of laboratory based work.
|Data Management, Data analysis and Statistics|
This course will provide an introduction to best practice in scientific data management and curation, and to systems to help students curate, manage and publish experiments. The importance of the full consideration of statistics in the planning, execution and reporting of science is also explained.
|Introduction to Image Analysis
Provides a practical foundation for image analysis for students from a broad level of technical ability. The course will introduce students to commonly used image analysis software packages analysis algorithms, with worked examples of analysis using real data.