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signaling models”. The scholarship is full-time for 2 years, with access starting in May 2026 or by agreement. The research will be carried out in the laboratory of Cemal Erdem at the Department of Medical
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industrial decarbonisation modelling to support the EU-funded FLARE project. The role will lead the technical development and integration of bottom-up, organisation-level decarbonisation models for energy
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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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digital twins be used to provide on-line predictions as to the future expected evolution of these critical properties as the basis for safe reinforcement learning (RL) for on-line optimal control”. In
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Postdoctoral Positions in PFAS Analytics, Degradation, and Thermophysical Properties - DTU Chemistry
thermophysical properties vary across the diverse PFAS chemical space and how these properties may be predicted using computational models. These positions offer an excellent opportunity for early‑career
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, aimed at uncovering the key traits that define successful microbial biofertilizers, and to develop predictive models that can guide the rational design of next-generation BioAg products tailored
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digital twins be used to provide on-line predictions as to the future expected evolution of these critical properties as the basis for safe reinforcement learning (RL) for on-line optimal control”. In
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, genomic selection modeling, bioinformatics, proficiency in R, Python and/or Linux command line • Experience with DNA/RNA extraction and library preparation • Experience working with large-scale datasets
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predictions of the models. Placement: La Rochelle Université, laboratory LaSIE, UMR 7356 CNRS Recruitment: fixed-term contract 12 months Working hours: full time Contract starting: Spring 2026 Salary: According
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 2 months ago
to the weather prediction and climate projections. This is mainly due to our lack of understanding of cloud/snow ice microphysics and over-simplified representation in models. On a broader sense, although weather