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Field
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: Help develop a non-invasive computer vision method to track and analyze how hens move in 3D space. You will gain hands-on experience in behavioural studies, animal welfare science, and innovative data
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the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description 1–2 PhD students in
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Temporary Job Status Full-time Hours Per Week 38 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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. This includes sample preparation, data collection, computational analysis, and 3D structure determination of protein macromolecules. Experience in cellular tomography workflows for EM analysis of cells and
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resistance and relapse. Our ultimate goal is to develop new anti-leukemic therapies. We are searching for a highly motivated and dedicated student with a strong background in molecular biology and/or cell
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experience in Computational Biology, Biostatistics, Bioinformatics, Computer Science, Data Science, or related discipline. * At least 1 year of experience in bioinformatics research. * Quantitative training
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Commission under the Horizon Europe framework programme (Grant Agreement number 101225682). The METAMIC 3 project will embed Doctoral Candidates in a unique training environment to advance microbiome science
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nanotechnology, photonics, biotechnology, synthetic biology and materials for energy storage and conversion, our faculty aims to provide solutions to important problems of the 21st century. To that end, we educate
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, including participation in coursework, journal clubs, and training events Your Profile Master’s degree (or equivalent) in neuroscience, biology, or a related discipline Proficiency in English (spoken and
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your doctoral degree: A dynamic, interdisciplinary research environment at the forefront of materials informatics Comprehensive training courses and individual opportunities for personal and professional