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). More information on the IMPRS faculty: https://www.molgen.mpg.de/IMPRS/fac . The mission of the Max Planck Institute for Molecular Genetics (MPIMG) is to lead scientific and technological breakthroughs
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Department:Biochemistry and Molecular Biology Salary Salary:$38,755.00 - $38,755.00 Position Details Full/Part Time Status:Full Time Percent Time:100% Position Description: The laboratory of Dr. Ksenia Krupina is seeking a
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career. Website for additional job details https://jobs.uni-graz.at/en/jobs/b6147d26-49c3-f6ac-6302-69a6e1d00728 Work Location(s) Number of offers available1Company/InstituteDepartment of Molecular
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translational projects employing single-cell sequencing, immune profiling, transgenic models, and molecular biology to uncover pathomechanisms and therapeutic targets in arthritis, osteoporosis, intervertebral
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therapeutic strategies. - DNA-protéines complexes modeling - Molecular dynamics simulations of biomolecules - Enhanced sampling techniques (Steered MD, Gaussian Accelerated MD) - HPC resources use - Scientific
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 days ago
in fields like immunology, genetics, epigenetics, molecular biology or biochemistry. Interest in doing research using mice as animal models. Good command of the English language. High degree
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, the postdoctoral researcher will be responsible for contributing to the development of advanced methodologies for predicting crystal structures (CSP) based solely on their chemical composition and atomistic modeling
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field A background in metabolism, liver biology, immunology, or systems biology Experience with animal models, molecular biology, or multi-omics approaches A strong publication record and the ability
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Website: https://med.stanford.edu/stankovic-lab.html (link is external) https://hellerlab-stanford.net/ (link is external) How to Submit Application Materials: Please send the following materials in a
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. The postdoctoral fellow will lead efforts to develop novel machine learning models for integrating omics datasets (e.g., genomic, transcriptomic, epigenomic, proteomic, metabolomic) with relevant molecular pathways