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The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences | Poland | 4 days ago
molecular biology techniques (independently and in collaboration with other team members), - Designing experiments and analysing data, - Writing manuscripts, - Participation in supervision of MSc and PhD
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and outreach. Co-supervision of PhD students, MSc and/or exchange students. Active contribution to group meetings and discussions. Share this opening! Use the following URL: https://jobs.icfo.eu/?detail
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We are looking for a highly motivated and dynamic Postdoctoral fellow with a PhD or equivalent degree to join the Merino Group at the Novo Nordisk Foundation Center for Basic Metabolic Research
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staff and ~60 Ph.D. students. Please read more about the department’s work at https://www.uu.se/en/department/cell-and-molecular-biology . The Elf group works across traditional disciplinary boundaries
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molecular approaches to address fundamental questions in synaptic physiology and pathophysiology. RESPONSIBILITIES Conduct and lead research projects in synaptic physiology and neuroscience, with
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. Job Requirements: PhD degree in Civil and Environmental Engineering or related field Relevant research experience on geotechnical engineering Relevant research experience in molecular dynamics
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experience on geotechnical engineering Relevant research experience in molecular dynamics simulations and computational fluid dynamics will be preferred. Excellent proposal writing and report writing skill
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of lung cancer genomics, transcriptomics, and molecular biology. The successful candidate will join a young, dynamic, and interdisciplinary team dedicated to uncovering the molecular mechanisms driving lung
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development (https://www.helsinki.fi/en/about-us/careers ). Required qualifications PhD (or near completion) in evolutionary biology, ecology, genetics, or related fields. Expertise in molecular genetics
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 30 days ago
complexes. The successful candidate will develop novel graph neural network (GNN) architectures to learn dynamic information from molecular dynamics (MD) simulations of protein-protein and protein-nucleic