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absorption/fluorescence and scattering experiments at X-ray free electron lasers. Your focus will be to derive new algorithms for interpretation of the scattering data by introducing chemical force-fields via
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EMBL Partnership for Molecular Medicine, which is dedicated to the growing field of life sciences that investigates the molecular basis of disease and explores molecularly and genetically based
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. The successful candidate holds/or are about to receive a Master of Science degree in computer science, data science, or a related area, and have strong background in algorithmic design, data mining, machine
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molecularly and genetically based treatments. Eligibility requirements Applicants meet the basic eligibility requirements for doctoral studies if they have: Completed a second-cycle (Master’s level) degree
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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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into how algorithmic systems influence the circulation of information and disinformation across digital platforms, and how such processes affect perceptions of credibility, truth, and democratic
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microbial ecology, biotechnology or microbiology. very good oral and written proficiency in English. excellent laboratory skills in microbiology. knowledge and related skills pertaining to genetically
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qualifications You have graduated at Master’s level in Biology/Medical Biotechnology/Genetics or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses Biology/Genetics
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providing interaction with researchers from diverse research fields and access to various scientific and technical expertise. Background and description of tasks We are developing genetic screening tools