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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
qualifications: Ph.D. in cancer biology, molecular biology, immunology, genetics, or a related field. Experience with cell and molecular biology techniques, animal models, immunology assays, or translational
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-1000, Slovenia [map ] Subject Area: Biophysics / Molecular biophysics Appl Deadline: 2026/03/02 04:59 AM UnitedKingdomTime (posted 2026/02/09 05:00 AM UnitedKingdomTime) Position Description: Position
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proteomic techniques as well as human stem cell models. The candidate must be comfortable with advanced molecular biology techniques and bioinformatics. We are seeking a self-directed, self-motivated, curious
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following disciplines: bacterial genetics, molecular cloning, gene editing approaches, host–pathogen interaction models, immunological assays (including cytokine analysis, flow cytometry, ELISA, Western
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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome
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: Doctoral degree conferred prior to start date Research experience in molecular biology, cell biology, biochemistry, iPSC models, mouse genetics Record of research productivity and publication Integrity
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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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Applications are invited for a postdoctoral position in the group of Dr Aleksandr Gavrin ( https://mbg.au.dk/a-gavrin/ ) at the Department of Molecular Biology and Genetics, Aarhus University
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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an excellent work ethic and background in molecular simulation and machine learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in