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Position: PhD Position in Machine Learning for Engineering of Therapeutic Proteins
Institution: Universität Basel
Location: Basel, Switzerland
Duties: Development and application of new machine learning models for the quantitative prediction of biomolecular interactions. Predictions will be validated and assessed using data derived from high-throughput next generation sequencing and directed evolution experiments
Requirements: Master of Science in relevant field (chemistry/biochemistry, physics, biotechnology, etc...) from an accredited institution; Strong interest/experience in protein engineering, directed evolution; Strong interest/experience in next-generation sequencing; Computer programming skills (python, MatLab, Linux, or similar)
   
Text: PhD Position in Machine Learning for Engineering of Therapeutic Proteins Position PhD position under the supervision of Prof. Michael Nash (co-supervisor: Anatole von Lilienfeld) at the Department of Chemistry, University of Basel. Project Development and application of new machine learning models for the quantitative prediction of biomolecular interactions. Predictions will be validated and assessed using data derived from high-throughput next generation sequencing and directed evolution experiments. Research Directed evolution is a laboratory method which mimics the incredible power of nature to evolve new types of biomolecular behavior under selective pressure. We are interested in combining high-throughput screening methods with directed evolution and machine learning algorithms to predict binding behavior of peptides to proteins of biomedical or therapeutic interest. The Nash Group specializes in single-molecule interaction studies on protein receptor-ligand complexes, and has developed new high-throughput screening methods for evolving molecular properties. The von Lilienfeld group specializes in machine learning, and high-performance computing with the goal of developing predictive methods which accelerate the computational design or discovery of new biomolecules. The PhD position will be jointly shared between the two labs. Details We have recently been awarded a Swiss Nano Institute PhD scholarship, and are now looking to hire an ambitious, driven, skilled and talented individual who would like to join our efforts. This PhD position is part of the SNI's PhD program which provides funding, networking opportunities, and helpful guidelines ( https://nanoscience.ch/en/research/phd-program/ ). Necessary skills and characteristics: Strong interest/experience in protein engineering, directed evolution Strong interest/experience in next-generation sequencing Computer programming skills (python, MatLab, Linux, or similar) For PhD position: Master of Science in relevant field (chemistry/biochemistry, physics, biotechnology, etc...) from an accredited institution. Offer Join our vibrant, interdisciplinary, and international research groups in Basel Collaborate with computational and experimental groups Experience a stimulating working environment: We are a member of the Institute of Physical Chemistry, the National Center for Molecular Systems Engineering, and the Swiss Nanoscience Institute. The Nash Lab is jointly affiliated with ETH Zurich Department of Biosystems Science & Engineering (DBSSE). We are collaborating strongly with other local groups from D-BSSE and University of Basel (Biozentrum & Chemistry) Competitive salary Basel is a city university (oldest university in Switzerland) with international flair (bordering France and Germany) and a strong ex-pat community, not only due to university but also due to Swiss Tropical Institute, Bank for International Affairs, big pharma companies, and arts community. Basel is very well connected with its own airport, and high-speed trains to Paris or Frankfurt. Application / Contact If you are interested in a position, please send your CV to Prof. Michael Nash (michael.nash@unibas.ch) together with a motivation letter and names and e-mail addresses of three references. www.unibas.ch
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