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protocols to characterize both cellular and vascular properties of the TME. The approach will be validated using a combination of in silico models, computer simulations, and in vitro experiments using tumor
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and a heterogeneous emerging computer architecture, collaborate regarding compiler and other tools as well as modeling their hardware for integration into the emerging computer architecture framework
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machine learning for time series, geospatial data or dynamic models; ideally experience with deep learning frameworks (e.g., PyTorch). Strong analytical and conceptual skills for designing and interpreting
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microstructures along the entire process chain using machine‑learning (ML) techniques and validate soft‑sensor outputs against laboratory reference measurements Perform systematic laboratory flotation experiments
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THE FIELDS OF: ATMOSPHERIC PHYSICS AND CHEMISTRY, ELECTROCHEMISTRY, ELECTROCHEMICAL ENERGY STORAGE (BATTERIES), ELECTRONICS, ELECTRICAL AND MECHANICAL ENGINEERING, HIGH-PERFORMANCE COMPUTING, MACHINE LEARNING
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Leibniz-Institut für Präventionsforschung und Epidemiologie – BIPS GmbH | Bremen, Bremen | Germany | 13 days ago
grants. Research areas of BIPS (and faculty members) include pharmacoepidemiology and cancer screening (Ulrike Haug), prevention and implementation science (Hajo Zeeb, Daniela Fuhr), biostatistics, machine
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), biostatistics, machine learning, data science and research data management, and causal inference methods (Iris Pigeot, Marvin Wright, Vanessa Didelez), and etiologic and molecular epidemiology (Konrad Stopsack
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knowledge with statistics, machine learning, Deep Learning and AI are an advantage • Good knowledge of the English language LanguagesENGLISH Research FieldEnvironmental science » Ecology Additional
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or Python) • Good knowledge of the English language • Experience with statistics, machine learning, Deep Learning and AI are an advantage • Familiarity with fundamental ecological concepts and experience in
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developing a digital twin, employing machine learning and numerical computations of atomistic processes. At IKZ, a kinetic Monte Carlo tool has been developed in the programming language julia. This allows a