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an outstanding Master’s (or equivalent) degree in experimental life sciences, computational/mathematical/biophysical sciences, or a related field. We seek individuals with a strong interest in
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project work plan and milestones Your profile Completed university studies (Master/Diploma) in the field of Chemical/Metallurgical/(Mineral) Process Engineering, Data Science, Statistics, Machine Learning
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production of bacteria via mass spectrometry Statistical analysis of the resulting data The successful candidate will have the opportunity to work towards a PhD Required qualifications: University degree (M.Sc
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, the details of the process are not yet fully understood. Mechanistic learning, the combination of mathematical mechanistic modelling and machine learning, enables a data-driven investigation of the processes
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algorithmic topics, including mentoring of M.Sc., B.Sc. or Diploma students Requirements: a university degree (M.Sc. or equivalent) or imminent M.Sc. degree in Computer Science, Mathematics, or a closely
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-related concept proposed by Robert Zubrin) or the solar-wind ion focusing thruster. Starting from first-principles and mathematical models, more advanced numerical tools shall be developed to explore
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to explain biological phenomena and disease mechanisms by leveraging biophysical theory and mechanistic, mathematical modeling. Our interests include the inflammatory responses to infection, the organization
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(M.Sc. or equivalent) or imminent M.Sc. degree in Computer Science, Mathematics, or a closely related field research experience, evidenced by publication(s) or a relevant M.Sc. thesis, good knowledge
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social scientists from a range of Leibniz research institutes in a new multi-year research project on antimicrobial resistance (AMR), including statistical and econometric investigations of country-level
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experience with methods of molecular biology and/or in the field of histology Experience in animal experimentation is an advantage Knowledge of statistical methods for data analysis Very good written and