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. In parallel with your experimental work, you would develop theoretical models in collaboration with our international collaborators. You would also develop advanced image analysis schemes to analyse
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colour centre spins. Your work supporting and further develops the fabrication of these chips, i.e. together with 1-2 PhD students, you will work on the sample process line involving several cleaning steps
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: Recently earned a Ph.D. in bioinformatics, computational biology, computer science, electrical and computer engineering, or a related discipline Strong experience in integrating several of the following
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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
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structure-adhesion relationships from characterization data Is Your profile described below? Are you our future colleague? Apply now! Education PhD in Material Science and Engineering or Material Chemistry
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. Qualifications PhD, MD, DO, or equivalent degree. Education and research experience in the areas of outcomes research. Successful applicants will have demonstrated success in research, scholarship, and/or grant
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programme designated to attract and empower the world’s brightest early-career researchers. This fellowship supports outstanding scientists who harness Artificial Intelligence (AI) to accelerate breakthroughs
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at Mount Sinai and the New York City area. The qualified candidate should have • PhD degree • Proficient experience with molecular biology-related experiments, cell biology-related
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for electron cyclotron heating at external facilities. Responsibilities and qualifications You hold a PhD in plasma physics or a closely related field and possess a strong experimental background, including
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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