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and drug–excipient interactions that determine formulation stability and performance. The research will employ atomistic molecular modeling grounded in statistical mechanics to investigate binding
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) within the Odense Child Cohort (OCC). PFAS levels have been measured during fetal life, and at 18 months and 5 and 7 years. The project does require biological knowledge and statistical skills
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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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, translational, and experimental approaches. The PhD student will work with patient cohort to perform biomarker analyses and statistical modeling of clinical outcomes. In parallel, the student will contribute
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to be fluent in English (written and spoken), hold a degree within epidemiology, statistics or a health-related discipline and have a track-record within the field of observational research, preferably
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and statistical concepts Proficient in English for technical writing, oral presentations, and general communication Additional experience (preferred) Very good knowledge of XAI techniques Thorough
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/ TensorFlow / Scikit Learn Highly knowledgeable in mathematical and statistical concepts Solid foundation in mathematics for Machine Learning (Linear Algebra, Probability, Optimization). Proficient in English
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in Demography, Social Science, Economics, Mathematics and Economics, Public Health, Statistics or similar. Furthermore, we expect applicants to: Have strong English skills, both spoken and written. Be