235 coding-"https:"-"Prof"-"FEMTO-ST"-"https:"-"https:"-"https:"-"Dr" Fellowship positions
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experimental tasks using Gorilla or other programs that can be used for online tasks. Align with and actively demonstrate the Code of Conduct and Values. Cooperate with all health and safety policies and
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it when applying. Candidates who advance to later stages of the process may also be asked to complete a coding exercise and provide contact information for a reference who can speak to their research
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this initial period. To be successful you will need a track record of developing, testing, and delivering high quality code to tight deadlines, to solve engineering problems. Ideally you will also have
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Max Planck Institute for the Study of Religious and Ethnic Diversity, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
Job Code: PIC20251126 Job Offer from November 26, 2025 TheMax Planck Institute for the Study of Religious and Ethnic Diversity studies central social science questions such as social and political
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Organization U.S. Department of Defense (DOD) Reference Code USAFSAM-2025-0004-F How to Apply Click on Apply at the bottom of the opportunity to start your application. Description The U.S. Air
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coding, including familiarity with data analysis and bioinformatics tools relevant to neurobiological research. Extensive experience supervising postgraduate students and supporting research teams
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experience includes developing Discrete Element Models (DEM) or hybrid models (e.g., DEM-CFD, DEM-SPH). A proven research record through publications and code development is required. We are seeking a
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learning or computer vision conferences/journals, such as TPAMI, IJCV, CVPR, ICLR, ICCV, ECCV, NeurIPS, ICML. Strong coding skills in scientific or engineering software like PyTorch, TensorFlow, Keras, etc
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Organization U.S. Department of Defense (DOD) Reference Code NAMRU-SA-2025-0004 How to Apply Click on Apply at the bottom of the opportunity to start your application. Application Deadline 11/20
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-Coding Genome Edits: Develop innovative machine learning approaches for designing precise non-coding genome edits, focusing on how non-coding alterations influence gene regulation and cellular function