60 computational-physics-superconductor PhD positions at Technical University of Munich
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, Mathematical modelling, Biology, Environmental Science, Physical Geography, or related fields. • Specific research in agricultural-environmental disciplines, and particularly with respect to livestock
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in Life Sciences or in Computational Biology • Experience in flow cytometry, cell culture and in high-dimensional single-cell data analysis and programming skills are a plus • Organizational skills and
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qualification program for PhD students containing excellent multidisciplinary training with tailor-made subject-based and soft skills courses, annual retreats, summer school, and a supervision concept. More
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well as chemistry and physics-based applications (www.bucherlab.org). We are currently exploring two different directions with two open positions: 1) Surface NMR spectroscopy. Recently we have applied NV-centers
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and an extensive server infrastructure for research Excellent training and career support opportunities (courses, personal coaching, ...) Your qualifications Master’s degree in Computer
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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journals. Close collaboration with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong
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infrastructure for research Excellent training and career support opportunities (courses, personal coaching, ...) Your qualifications Master’s degree in Computer Science or a similar field Good theoretical
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: - Master in chemistry, physics, material science, engineering, or a closely-related field - You have experience/interest in electrochemistry (electrocatalysis, plating, corrosion…) - Knowledge/Interest in
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the developed code Publishing the developed approaches in international journals and conferences Requirements Promising applicants have: A master’s degree in Computer Science, Geodesy, or related discipline Very