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Field
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for this position will be included in a Job Pool that may be considered for future project requirements Eligibility criteria Training and experience in physical-mathematical modelling of complex biological systems
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 20 days ago
or almost completed) in Physics, Applied Mathematics, Complex System or a related field. Strong background in mathematical modeling, machine learning, or biophysical simulations. Demonstrated interest in
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Details Title Postdoctoral research fellows in generative, multimodal AI, and seismic foundational models School Faculty of Arts and Sciences Department/Area Earth and Planetary Sciences Position
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, Industrial Engineering, Applied Mathematics, Data Science, or a closely related field. Experience with system dynamics modeling (Stella, Vensim, Powersim, or similar). Strong quantitative and analytical skills
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models (mathematical + software) of existing grid operational practices Systematically exploring different formulations of mixed-integer constraints in grid optimisation problems Developing machine
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of Immunity – Artificial Intelligence (CoI-AI) Programme, a pioneering initiative that integrates controlled human infection models, advanced immunology, and AI-driven analytics to accelerate vaccine discovery
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methods and research software empower modern biomedical research. Your mission As a Postdoc you will help build the next generation of multimodal and explainable AI models for personalized risk prediction
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analysis Large language models or machine learning/predictive modeling for longitudinal data analysis Strong computer programming skills Strong mathematical or statistical skills Ability to work as a part of
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About the Opportunity Job Summary Working under the supervision of Professor Ken Duffy, the Department of Mathematics at Northeastern University is seeking a Postdoctoral Research Associate to work
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, modulation classification, sensing, and adaptive spectrum optimization in diverse operational environments. Your work will focus on modeling and algorithmic aspects related to the development of highly