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qualifications include: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering or a related field; Strong background in Deep Learning (e.g., Transformers, foundation models); Strong programming
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Postdoctoral Positions in PFAS Analytics, Degradation, and Thermophysical Properties - DTU Chemistry
may be obtained: From Professor Charlotte Held Gotfredsen, tel.: +45 20650942, email: chg@kemi.dtu.dk with respect to position 1 and 2. Website: https://www.kemi.dtu.dk/english/research/organic
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research infrastructure A competitive salary and social benefits (e.g., health coverage, parental leave, social security, etc.) (https://www.sdu.dk/en/om-sdu/international-staff/getting-settled ) Workplace
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in Computer Science, Machine Learning, Artificial Intelligence, Computational Biology, or a closely related field Has strong theoretical and practical experience in deep learning Has hands
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for the human societies https://www.sdu.dk/en/forskning/sdu-climate-cluster . The work language is English. If the application is successful, the postdoc candidate will be based at SDU with opportunity of a
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see the full call, including how to apply, on https://fa-eosd-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/da/sites/CX_1001/job/3637/?utm_medium=jobshare
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likely use ICP-MS to measure catalyst degradation in the electrolyte after testing. The potential to teach, advise Bachelor/Master student thesis projects, or be involved in proposal writing is also
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University (http://bio.au.dk/en) and work in the Section for Microbiology at this department. The section employs 12 permanent scientific staff and ~20 PhD students and postdocs. Research at the section covers
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students. The department is responsible for two educations: Molecular Biology and Molecular Medicine with a yearly uptake of 160 students in total. Please refer to http://mbg.au.dk/ for further information
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imaging, deep proteomics, metabolomics, metaproteomics, and machine learning (ML) approaches to develop diagnostic classifiers, spatial tissue atlases, and identify potential therapeutic targets