301 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Nature Careers
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, specifically the biomedicine modules. Your profile as postdoc We seek a candidate at PhD level or equivalent, with a background in biology, animal science, veterinary science, or similar with special interest in
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
the current management concept adequately address the emerging challenges posed by climate change and a fast-growing fishery? How can the management concept be improved, potentially by learning from management
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live in. Your role Research related to the following areas: Mathematical statistics, Machine Learning, High-dimensional statistics, Robust estimation methods, Probabilistic foundations of mathematical
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publication background. Application instructions If you are interested, please email your CV, a statement of your research interests, and names of three references to Dr. Jian-Fu (Jeff) Chen, PhD at Jianfu
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presentations at international conferences Our requirements Completed PhD in Biology, Biotechnology, Bioinformatics, Immunology, or related field Strong interest in computational science and AI (prior formal
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interpretation of OMICs datasets (DNA, RNA, proteome) Supervision and technical guidance of Bachelor’s, Master’s, and PhD students, as well as technical staff within the project context Participation in teaching
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preclinical in vitro and in vivo models Supervise and mentor MSc/MD/PhD students Collaborate with national and international research partners Present your results at scientific meetings Publish your findings
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Applicants should hold a PhD degree in Biochemistry or Molecular Biology and have experience in protein O-GlcNAcylation modification field. Requirement: At least five years of research experience in fly
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, and abroad. Required qualifications: The candidate should have a PhD in condensed matter physics, with strong background in high vacuum, cryogenics, electronics, transport and magnetic measurements
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission