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John Curtin School of Medical Research · ANU College of Science and Medicine
The deluge of data from our newfound ability to sequence genomes and visualise molecules from thousands of cells and individuals will revolutionise healthcare. Computational solutions, from distributed computing to deep learning, are increasingly essential to biomedical progress. While the transformation at the interface of high-throughput experimentation and computer science is underway, biomedical research is generating data at a faster pace than we are able to process and interpret it. This presents an unheralded opportunity for motivated students to become the new leaders of the computational biology revolution. This course is an opportunity for students with diverse disciplinary backgrounds — including but not limited to computer science, engineering, statistics, biology, physics and mathematics — to work on real-world biomedical problems using computational methods under the supervision of top researchers at the John Curtin School of Medical Research (JCSMR). This course will embed students into multidisciplinary teams to identify and work on applications of innovative computational technologies to biomedicine. This course can be taken as either 6 or 12 units. Students who take the 12 unit version are expected to undertake more in-depth and sustained study.
Project Proposal
Learning outcomes 1, 4
Software Output
Learning outcomes 1, 2, 4
Final Report
Learning outcomes 1, 2, 3, 4, 5
Oral Presentation
Learning outcomes 3, 5
This course is available as 6 or 12 unit course. For each 6 units of enrolment, the expected minimum workload will consist of approximately 130 hours of total student learning time made up of independent student research, reading and writing. Students are expected to maintain regular contact with their supervisor and attend all supervisory meetings. The expected workload if taken as a 6 unit course will consist of approximately 130 hours throughout the semester including approximately 65 hours of team meetings, event preparation and self-directed study, including developing skills in developing and/or using software tools, and 65 hours of computational design and data analysis. Students are expected to actively participate and contribute towards group scientific discussions, presentations in group meetings, and attend school seminars. Work Integrated Learning Projects Students may engage with WIL partners (internal/external) as a component of the course. Other Information Admission to this course is subject to availability of a suitable supervisor and approval from the Course Convener. Further details about potential supervisors and projects can be found via the JCSMR website: Talo Computational Biomedicine Courses | The John Curtin School of Medical Research (anu.edu.au) Students must complete the Research Project Summary Form which can be obtained from the JCSMR HDR Student Administration Team by email (jcsmr.hdr.sa@anu.edu.au) and submitted via the following link: https://students.science.anu.edu.au/program-admin/requesting-permission-enrol There is a financial award available from the JCSMR Talo Computational Biology Talent Accelerator. Selection for an award will be based on academic merit.
None Preliminary Reading An Introduction to Bioinformatics Algorithms. N.C. Jones & P. A. Pevzner. MIT Press. 2004 (https://books.google.com.cu/books?id=p_qzpkNVcUwC) Mathematics for Machine Learning. Copyright 2020 by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. Published by Cambridge University Press (https://mml-book.github.io/)