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biological and epidemiological questions. Write up the research findings for publication in top-tier scientific journals and conferences. Qualifications Ph.D. in computer science, statistics, epidemiology
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The Robotic Materials group at ETH Zurich Department of Materials is looking for three postdocs and one PhD for the project funded by ERC Starting Grant : "Distributed Addressable Robotic Material
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room for flexibility in both directions. We are seeking a highly motivated individual with a PhD in computer science, computational chemistry / biochemistry, applied mathematics, or a related area. The
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from over 50 nations, it is the largest institute of the Max Planck Society. The Research Group Computational Biomolecular Dynamics (Prof. Dr. Bert de Groot) is inviting applications for a PhD Student or
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at scientific conferences. Mentor graduate students and contribute to the overall growth of the laboratory. Qualifications: Ph.D. in Biomedical Engineering, Computer Science, Neuroscience, or a related field
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Engage in teaching as required Required Qualifications PhD in Bioinformatics, Computer Science, Physics, Engineering, Bio-engineering, or equivalent Excellent track record in Bioinformatics with at least
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Post Doctoral Researcher in Human-centred Large Language Models for Software Engineering, Departm...
collaboration within the Software Engineering group, and potentially across other research groups in the SECS Section. Your profile Applicants should hold a PhD degree in Computer Science or related field
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Bioinformatics, Molecular Biology, Biochemistry, Computer Science, or related field Special Skills, Knowledge, and Abilities: Required: Candidates must hold a doctoral degree (PhD, MD, or equivalent). Applicants
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outstanding postdoctoral researchers in the fields of Physics, Chemistry, Mathematics, Computer Science, Earth Science and the Life Sciences. This collaborative program offers a comprehensive four-year position
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PhD Degree in a relevant scientific field (e.g. computer science, data science, mathematics, engineering, or related); Strong understanding of generative models (e.g., VAEs, GANs, transformer-based