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Field
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, to target the patient’s specific condition and obtain an optimal long term outcome. FEM coupled with Design of Experiment (DoE) will guide the design of miniplates. Ad-hoc tuning of published
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optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature
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of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have recently completed (or be close to completing) a PhD in Computer Science, Machine
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motivated post-doctoral associate (or research scientist for experienced candidates with 5 years of post-PhD experience). The candidate will work under the supervision of Future-GRID TecH director Dr. Mohamed
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community. Main Tasks and responsibilities: Collaborate with theoretical and experimental partners to design and characterize optimized altermagnetic devices for information processing. Fabricate nanodevices
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systems that fuse multi-modal remote sensing, soil and phenology data to enable crop classification and precise, customized fertilizer recommendations. Selection criteria (short) Required PhD (awarded
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of research excellence is expected. Strong French and English communication skills, both verbal and written, are required. Key duties: Successful candidate is expected to: Develop and optimize lipid
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modelling toolkits that enable optimal design and operation of greener vessels, backed by real-world demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling
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complex endometrial models and optimizing in vitro implantation assays. Culturing human embryos and generating stem cell-based embryo models. Tissue sectioning for advanced spatial transcriptomic analysis
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to joint research activities, publications, and surveys. Requirements PhD degree (or near completion) in robotics, control, machine learning, or a related field; Strong publication record demonstrating