Applications are invited for an interdisciplinary postdoctoral position in the group of Dr. Gabriele Schweikert. This research opportunity focusses on exploring machine learning methodologies for computational biology and is funded by an Academy of Medical Sciences Award.
The overarching aim of the project is to develop dedicated Machine Learning tools that will promote our understanding of epigenomic patters. Epigenetic mechanisms allow eukaryotic cells to change their chromatin structure, providing phenotypic plasticity and enabling adaptive responses. These mechanisms leave measurable marks on the genome, including post-translational modifications of histone proteins (PTMs). Hundreds of proteins are implicated in writing and reading these complex, dynamic patterns, which are thought to constitute a ‘histone code’ that instructs dynamical cellular processes, such as transcription. To understand individual epigenetic components, their interactions and their impact on gene expression, we aim to extract relevant signals from high-dimensional, redundant data by developing sophisticated machine learning tools.
The successful applicant will be based in the Computational Biology Division of the School of Life Sciences at the University of Dundee. The School has been ranked the top university department in the UK for Biological Sciences (REF2014) and its global impact in Biomedical and Health Sciences for its size is 8th in the World (2019 CWTS Leiden Ranking). It boasts a range of world-class research facilities along with a vibrant interdisciplinary community of leading experts in chromatin biology.
The Schweikert lab has a second base at the Cyber Valley Initiative, which is a national hub for ML around the Max Planck Institute for Intelligent Systems and the University of Tuebingen in Germany. The successful applicant will have the opportunity to spend time at both locations exploiting a large number of opportunities for collaborations.
There will be extensive opportunities for interdisciplinary training, development and public outreach.
• PhD in Computer Science, Computational Linguistics, Mathematics, Statistics, Computational Biology or a related field, with an outstanding track record and at least one first-authored publication in an internationally recognised peer-reviewed journal.
• Must be capable of working in a team, but also plan and work independently.
• Interest to work interdisciplinary across the machine learning - life sciences interface.
• Excellent communication skills across disciplines and proficiency in spoken and written English.
• Strong background in Machine Learning (specifically: unsupervised learning, causal inference, spatio-temporal data analysis, grammar induction)
• Experience in computational biology
• Strong programming skills in a suitable language e.g. Python/ Tensorflow/ R/ C/C++ Matlab.
The position is available for up to 2 years depending on start date. The starting salary for this post will be between spine points 29-33 (£32,236 - £36,261) on the Grade 7 salary scale, depending on experience.
For informal enquiries, please contact Gabriele Schweikert (email: firstname.lastname@example.org).
Appointment as a Postdoctoral Research Assistant on the Grade 7 salary scale is dependent upon you having been awarded a PhD. An appointment may be considered if you are shortly expected to be awarded a PhD. The initial appointment will be made as a Research Assistant on the Training Grade 7 salary scale (Spinal Point 28, £31,302).
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