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Profile: University degree (M.Sc., diploma or equivalent) in materials science, engineering sciences, or physics Experience in at least one of the methods of X-ray imaging, transmission electron microscopy
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are currently about 200 EUR per semester. This includes use of local public transport free of charge from Monday to Friday (in the evenings), on weekends and on public holidays. In addition, students may purchase
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TRON – Translational Oncology at the University Medical Center of the Johannes Gutenberg University Mainz • | Mainz, Rheinland Pfalz | Germany | 15 days ago
contract with BioNTech or TRON. Academic admission requirements A Master’s degree in biology, biochemistry, chemistry, life science, medicine, immunology, computer science, engineering or related fields from
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the life sciences, medicine and related disciplines such as medical engineering, veterinary medicine and epidemiology. The doctoral candidates work closely with a thesis advisory committee to define
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at the participating laboratories, including platforms for NMR, X-ray crystallography, cryo-EM, and light microscopy; the Genome Centre with next-generation sequencing technology; and the Proteome Centre Tübingen
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semester and is largely tailored to the needs of PhD candidates. The current course offers can be found on the IMPRS-ESM website. Doctoral candidates are required to obtain 12 IMPRS-ESM credit points before
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, physics, and chemical engineering sciences to cultural heritage. A strong emphasis is placed on the mathematical and computational foundations, encompassing theoretical underpinnings and computational
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Management (SLUSE) IPB: Natural Resources and Environmental Sciences (NRES) UPM: Environmental Biotechnology/Environmental Engineering/Environmental System and Modeling UGM: Planning and Management of Coastal
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employment: as soon as possible Duration of employment: 3 years Working time: 29 h 52 min (75 %) Application deadline: 2025-07-30 Code number: 326-25 Your main tasks Participation in the DFG-funded project
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages