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learning Distributed and federated training The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another
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of machine learning Distributed and federated training The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics
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committed candidates from varied backgrounds who are eager to contribute to cutting-edge and interdisciplinary research. Successful applicants will ideally have: A relevant MSc degree in computer science
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of skills, and have the opportunity to explore interests in polymer synthesis, assay development, immunology, and statistics. Specifically, the work will involve: Organic synthesis Assaying polymers
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scholarship within the field of health science. We are looking for a person with a relevant degree (MD, MSc. etc.) Research environment We offer an attractive, flexible and inspiring work environment with
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part in teaching and supervision at BSc and MSc level, and to take responsibility in grant application writing. We seek a candidate with knowledge of the application and analysis of Sensory & Consumer
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. Applicants with interests and experience in any of galaxy formation, Lyman-alpha absorption, ISM/CGM evolution at high redshifts, JWST NIRSpec spectroscopy, ALMA spectral data, and statistical inference
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, MSc or PhD level Experience in contributing with writing research proposals for external funding Networking experience Additional qualifications Further, we will prefer candidates with some of the
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. Strong Competences in study design and data analysis, including multivariate data analysis utilizing advanced statistical analysis tools Proven publication record in international peer-reviewed journals
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techniques Ability to support non-bioinformaticians and deliver training in WGS data analysis. Skills in data management, visualization, and statistical analysis. Proven ability to plan and execute complex