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are planned for participation in several international conferences). Expected skills Knowledge and technical skills: • Master's degree (or engineering degree) in Evolutionary Biology, Ecological Modeling
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of estimators, test statistics, and predictions modelling dynamic relationships between brain activity and subjectively experienced pain at the individual level Research context The PhD is closely linked
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to crack initiation and assess the influence of the microstructure of Almelec alloys. The results will also be used to improve a predictive FEM model (Abaqus/Python) simulating crack initiation and
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Plant species distribution models (SDMs
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state‑of‑the‑art structure prediction and design frameworks, training/fine‑tuning models, and running scalable computational campaigns. Key responsibilities Design and execute in silico protein and
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charging) Predictive charging planning algorithms Railway Smart Pricing models Techno-economic evaluation versus the traditional catenary model This is applied research with validation in simulated
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 11 days ago
to improve the prediction of electric vehicle (EV) mobility patterns, energy demand, and state of charge (SoC) over time and space. The work will include the design of advanced modeling frameworks integrating
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Description About the position We are looking for a motivated PhD candidate to join a multidisciplinary research team working on predictive modeling of clinical outcomes after Deep Brain Stimulation (DBS) in
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well as interpretability of scientific foundation models. The rush to build foundation models has led to the development of large machine learning models in Astrophysics, fluid dynamics, biology, weather prediction, solar
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A postdoc position is available immediately in the laboratory of Dr. Daniel Blair which focuses on leveraging high-throughput chemical synthesis and MS/MS analysis to create predictive models