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Position: Postdoctoral Researcher - Join us to develop machine learning approaches to decipher principles of biological organization!
Department: Biozentrum - Center for Molecular Life Sciences
, Basel Switzerland
Duties: A postdoc position is available to develop machine learning approaches to infer cellular-level principles of biological organization from large scale data
Requirements: We are looking for a postdoctoral researcher with background in computer science, physics, or applied mathematics who is interested in developing and exploring applications of machine learning to integrate multi-omics data to infer principles of gene expression control and resource allocation in mammalian cells
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The Biozentrum of the University of Basel is one of the leading life sciences institutes in the world. It consists of 30 groups and 500 employees that research how molecules and cells create life, spanning the scale from atom to organism. Founded in 1971, the Biozentrum has been the birth place of many fundamental discoveries in biology and medicine, spawning several Nobel Laureates. A postdoc position is available in the group of Prof. Mihaela Zavolan at the Biozentrum, University of Basel to develop machine learning approaches to infer cellular-level principles of biological organization from large scale data. How do cells adjust their gene expression to coordinate movement, growth, proliferation, differentiation depending on available energy resources and external signals? Our interdisciplinary group studies the gene expression regulatory networks that are associated with cellular functions such as proliferation, differentiation, aging, using a combination of low and high-throughput experiments along with data analysis and mathematical models. However, in spite of the progress in identifying molecular mechanisms, we are still far from understanding the flow of information between regulatory layers that ultimately yields well-defined and distinct cell types, with characteristic functions. The resounding success of machine learning in predicting protein structure or the activity of various types of reporters prompts the question of whether it can also reveal higher-level organizational principles, which may allow us to more effectively control pathogenesis and thereby improve human health. Your profile We are looking for a postdoctoral researcher with background in computer science, physics, or applied mathematics who is interested in developing and exploring applications of machine learning to integrate multi-omics data to infer principles of gene expression control and resource allocation in mammalian cells. We offer We are a highly interdisciplinary, international and supportive team of scientists, where you will have the opportunity to broaden your horizons, develop new ideas, and engage other team members in implementing and testing your ideas in experimental systems. The fields that we are currently exploring with an extensive network of collaborators are aging and cancers. At the Biozentrum we have access to state-of-the-art facilities for systems-level interrogation of biological systems and a computational infrastructure to match the demands of big data science. Basel is an international city with people from 150 nations. Located on the border where Switzerland, Germany, and France meet, Basel is home for a large number of institutions for biomedical research, with numerous possibilities for training, networking and career development. The city provides a high standard of living and a rich and varied cultural atmosphere. Application / Contact Please submit your application letter, a statement of research interests, CV, and the contact information of at least two references to: Prof. Mihaela Zavolan Biozentrum Universität Basel SIB - Swiss Institute of Bioinformatics Klingelbergstrasse 50-70 4056 Basel, Switzerland email: mihaela.zavolan(at)unibas to make life hard for spam bots .ch Check out a few of our recent publications 1. Molecular and phenotypic analysis of rodent models reveals conserved and species-specific modulators of human sarcopenia. Börsch A, Ham DJ, Mittal N, Tintignac LA, Migliavacca E, Feige JN, Rüegg MA, Zavolan M. Commun Biol. 2021 Feb 12;4(1):194. doi: 10.1038/s42003-021-01723-z. 2. The neuromuscular junction is a focal point of mTORC1 signaling in sarcopenia. Ham DJ, Börsch A, Lin S, Thürkauf M, Weihrauch M, Reinhard JR, Delezie J, Battilana F, Wang X, Kaiser MS, Guridi M, Sinnreich M, Rich MM, Mittal N, Tintignac LA, Handschin C, Zavolan M, Rüegg MA. Nat Commun. 2020 Sep 9;11(1):4510. doi: 10.1038/s41467-020-18140-1. 3. A rare codon-based translational program of cell proliferation. Guimaraes JC, Mittal N, Gnann A, Jedlinski D, Riba A, Buczak K, Schmidt A, Zavolan M. Genome Biol. 2020 Feb 27;21(1):44. doi: 10.1186/s13059-020-1943-5. 4. Protein synthesis rates and ribosome occupancies reveal determinants of translation elongation rates. Riba A, Di Nanni N, Mittal N, Arhné E, Schmidt A, Zavolan M. Proc Natl Acad Sci U S A. 2019 Jul 23;116(30):15023-15032. doi: 10.1073/pnas.1817299116. 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