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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required
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05.07.2026, Academic staff Our research combines mathematical modeling, numerical simulation, scientific computing, and data-driven methodologies to improve the predictive capabilities and
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energy systems and demand response; process and energy system modeling; optimization and model predictive control; and applications of artificial intelligence and machine learning to energy systems
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to develop predictive models for polymer-based materials. This project aims to leverage computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 2 months ago
and applying numerical models to derive the mechanical properties of irradiated materials from micromechanical measurement data, e.g., microstructure-based prediction of hardness profiles or extraction
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metadata, and clinical imaging workflows. Experience with image classification, segmentation, temporal modeling, representation learning, multimodal learning, or clinical prediction modeling. Familiarity
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leakage and the project ACE Water, in the topic degradation in LTEL and HTEL stacks and developing lifetime models, life-time predictions and the validation of them. You will be expected to contribute
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. … Where to apply Website https://www.academictransfer.com/en/jobs/363299/postdoc-predicting-mitigating-l… Requirements Additional Information Website for additional job details https
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the earth sciences. NCCR Genesis does not aim to provide answers in all fields, but to drive innovative research and achieve decisive progress. Details on NCCR Genesis are available on its website https
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the growth of carbon chains. • Collaborate with astrochemists and observers to validate theoretical predictions. This position will focus on modeling dust production in supernova explosions, a key process for