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polygenic risk scores, rare variant burden scores, and integrative prediction models. Evaluate model performance and clinical utility. Identify therapeutic targets and causal risk factors for cardiovascular
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–2023), the model demonstrated good predictive performance for daily and weekly dengue cases based on two years of sentinel hospital data. As part of the ANRS SEA-ROADS programme (2024–2027), coordinated
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defects, are currently a major limiting factor for metal printing. In nanomedicine, various nanoparticles are used for controlled drug delivery and therapies, and laser-excited nanobubble-inducing shockwave
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, product management work, and and leadership responsibilities • Familiarity with artificial intelligence and machine learning approaches, including predictive modeling and precision analytics applied
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they change through time. To translate eBird observations into robust data products we create custom modeling workflows designed to fill spatiotemporal gaps based on remote sensing data while controlling
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commercial and open source cloud computing platforms designed to support the development of predictive analysis models. In addition, he/she will design and implement backend and frontend software
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unsupervised learning Distributed / decentralised command and control: synchronisation, coordination, adaptation, for example using multi-agent systems Decision support under uncertainty Modelling and simulation
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, AtomGPT). Working Knowledge Of: • Workflow tools (e.g., ASE) and HPC environments. • Software development in Python, Git-based version control, and Conda packaging. • Data integration and surrogate modeling
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Engineering of Catalysts for Hydrofunctionalization Reactions: From Selectivity Control to a Predictive Model” project financed from the funds of Priority 2 of the European Funds for a Modern Economy Program
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already been awarded a PhD degree. Selection process You should submit your CV through a dedicated site: https://cv.newton-6g.eu/ Additional comments Position: Data-driven models for CF networks