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Field
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strong background in Artificial Intelligence (AI), particularly in the development and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal
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Announcement - Mohammed VI Polytechnic University (UM6P), AgroBioSciences (AgBS) Job Title: Post-Doctoral in Modeling and Crop Yield Prediction in Africa Area of specialization: Agronomy, Modeling, biostatistics
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 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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at Tilburg University, in collaboration with the Faculty of Military Sciences and the Joint Sigint Cyber Unit, invites applications for a fully funded postdoctoral position focusing on predictive modelling
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Responsibilities: Develop a predictive model integrating the direct and indirect costs of urbanization. Calibrate this model using real data from specific case studies. Simulate urbanization costs based on various
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models are deeply rooted in real-world biological data. The collaborative approach allows for the development of predictive models that bridge the gap between theory and experiment, with a focus on high
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thermomechanical processing and develop computational models to predict mechanical properties, their evolution, and formability. Through August 2026, contribute to the DOE ARDAP research project by evaluating
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quantitative and machine learning approaches ● Developing predictive models linking nuclear features to future cell fate ● Interacting with collaborators in imaging, computational biology, and developmental
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. This approach enables UM6P to strengthen Morocco’s leadership in these areas through a unique model based on partnerships and by fostering the development of skills essential for Africa’s future. Located in
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exploration. The MULTISPIN project aims to advance this field by establishing predictive models and assessing the circuit-level behavior of MFTJ devices based on van der Waals (vdW) two-dimensional (2D