223 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Université de Bordeaux " Postdoctoral research jobs at Nature Careers
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of personal background. Apply online https://fa-eosd-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/jobs/preview/3538
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you continue pursuing your scientific career. More info and application: https://raeslab.sites.vib.be/e... We offer VIB-KULeuven is an exciting, interdisciplinary research institute with excellent
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. The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background. Apply online https://fa-eosd-saasfaprod1
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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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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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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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. 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