241 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" Postdoctoral positions at Nature Careers
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the usual documents until 1/11/2026 on the application portal of the university using this link: http://obp.uni-goettingen.de/de-de/OBF/Index/76205 . For more information get in touch with Serena Müller
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Requirements: * A brief, one-page description of project; we encourage a graphical abstract *Cover Letter * CV * Brief letter of support from Princeton faculty mentor (one page) Apply at https
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5-year undergraduate nanotechnology programme and nanoscience graduate programme (https://phd.nat.au.dk/programmes/nanoscience/) the center provides a full educational environment. In
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application of magnetically enhanced electrocatalysis for water splitting and CO2 reduction (see e.g. https://doi.org/10.1038/s41560-019-0404-4). Your main tasks may include Application of new materials and
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personality. The Department of Biology The Department of Biology (http://bio.au.dk/ ) provides a framework for research and teaching in all major biological subdisciplines. The department is especially known
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Project Description: Drug toxicity and resistance are the leading causes of therapeutic failures. The Chen Lab (https://www.stjude.org/research/labs/chen-lab-taosheng.html) studies: (1) the chemical
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vitae, a brief cover letter outlining their research experience and interests, and contact information for three references via email to: sgong@engr.wisc.edu Research Group Website: https
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. The successful candidate will be employed at the Department of Computer Science of the University of Luxembourg and have access to high-performance computing resources suitable for large-scale machine-learning and
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The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we, together with a leading external pharma company party, are seeking a
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Postdoctoral Research Associate - Hybrid Computational-Experimental Scientist in Bacterial Drug Resp
to antibiotics and host-like conditions. • Develop and apply statistical or machine-learning methods for interpreting single-cell and genomic datasets. • Work closely with wet-lab scientists to design perturbation