Studierende finden an der ETH Zürich ein Umfeld, das eigenständiges Denken fördert, Forschende ein Klima, das zu Spitzenleistungen inspiriert.
The Computational Biology Group at the Department of Biosystems Science and Engineering of ETH Zurich in Basel develops mathematical and statistical models and efficient algorithms for analyzing high-throughput molecular profiling data. We are particularly interested in evolutionary dynamics, including genomic and transcriptomic variation in viruses and tumors.
We have an opening for a PhD position in the field of computational oncology. The project focus is on elucidating tumor progression in acute myeloid leukemia (AML). Starting from longitudinal molecular data from targeted next generation sequencing, we aim to model the clinical outcome of patients undergoing stem cell transplants.
To model the clinical outcome of patients undergoing stem cell transplants, we will need to develop a novel statistical methodology for interaction and progression networks, which integrates clinical covariates.
Moreover, we wish to build a prediction model for patient response to specific therapies, which we then plan to validate against in vivo treatment response in a pre-clinical animal model, and eventually establish a genetic-functional assays platform that may lead to personalisation of treatment in AML and improved patient outcome.
Successful applicants have a strong quantitative background in computational biology, statistics, computer science, physics, mathematics, or a related field. Exposure to modeling biological systems and experience in developing software for their analysis are highly advantageous. Candidates are expected to engage in interdisciplinary re-search teams and to foster collaborations with computational biologists and clinicians.
We look forward to receiving your online application with a letter of motivation, CV, diplomas and contact details of at least 2 referees. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Further information about The Computational Biology Group can be found on our website .
26-03-2024
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