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researcher in structural bioenergetics (m/w/d) Your tasks Production, purification and downstream optimization of terminal oxidase samples for structural studies via cryoEM. Stable adjustment and spectroscopic
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Job Description Are you interested in a postdoc position working on establishing and optimizing reliable methods for producing yeast-based cell-free protein synthesis (CFPS) extracts in
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
is designed for candidates who have completed their PhD within the last two years and have experience as postdocs or industry researchers. This position offers a 12-month term with potential
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-optimization… Requirements Specific Requirements PhD in Electrical Engineering, Applied Physics, Operations Research, Computer Science, or a related discipline, with a focus on quantum algorithms. Knowledge
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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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protocols to our Workflow Performing microscopy experiments on sperm dynamics under various controlled environmental conditions Merging experimental results, simulations, and literature for optimal conditions
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experiments, including occasional wet lab work Merging experimental results, simulations, and literature for optimal conditions inducing movement differences, in collaboration with the team. Participation in
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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engineers – on average 10 people - led by Magdalena Calusinska, dedicated to advancing microbial biotechnology through multi-omics approaches, bioinformatics, and process optimization. As post-doctoral
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intelligence (AI) for application in medicine, with a primary focus on optimizing clinical trial design. The partnership will bring together the University of Oxford’s expertise in statistics, mathematics