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, optimize, and analyze high throughput functional assays and pooled library screens Help with the validation of candidate variants and genes in mouse models Analyze data using relevant software and present
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, while working in an ambitious, motivated, and multi-disciplinary team of veterinarians, clinicians, material scientists, biologists, and engineers. You will also participate in the co-supervision of PhD
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will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and help supervise associated PhD students. The successful candidates will join large, supportive
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, such as AI providers and data center operators, to evaluate and compare scenarios to reduce emissions. The framework will be released as a software tool to guide emissions reduction strategies. The project
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of the research group, including postdocs, research assistants, technicians, PhD and project students, as well as to represent the PI and ISML when required. You will hold a Masters or PhD degree (or be close to
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institution and they are allocated through recurrent internal calls). Preparation of scientific reports, journal articles and software documentation. Requirements: PhD in Physics, Materials Science, Chemistry
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guidelines for the Postdoctoral Appointee-mentor relationship. Prompt disclosure to the mentor regarding the possession and desire to distribute materials, reagents, software, copyrightable and potentially
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be available. Position Description A PhD degree in one the fields: plant biology/ genetics, human nutrition, physiology, nutritional epidemiology, biotechnology, genetics, or food systems, or other
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in the research and management of the Computational Materials Discovery group. You supervise and guide students at the bachelor, master and PhD level. You contribute to the teaching activities in
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will work on multiple projects funded by NIH/NHGRI. The objective of the position is to develop novel statistical methods and computer software and analyze large scale biological data from biobanks