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psychological attributes), as well as secondary data analyses in large scale ongoing cohorts evaluating biobehavioral mechanisms by which optimism may lead to healthier aging. Additional work will include
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, and large-scale inference workflows. The project engages UK-government stakeholders, reflecting its policy relevance. Applicants should hold a postgraduate degree, ideally a doctoral degree in computer
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, mechanistic studies and rigorous analytical characterization under the project “Sustainable Chemistry for High-Value Glycoside Products via Traceless Activation.” Key Responsibilities: Design and execute multi
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methods for reasoning over multi-agent interactions. This Research Assistant position will contribute to research exploring how temporal knowledge representation, abductive and probabilistic reasoning and
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: • Develop real-time optimization algorithms; • Model multi-vector energy-water-hydrogen systems; • Support the development of digital twins; • Test the algorithms using operational data; • Prepare a technical
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translational oncology. Design, execute, and oversee complex experimental protocols, including in vitro, in vivo, and multi-omics approaches. Supervise and mentor postdoctoral researchers, Ph.D. students, and
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expertise in infrasound signal processing to advance our multi-sensor atmospheric observation programme. About the Role: This position is an opportunity to join an active and forward-looking research team
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the attribution of (1) research grant within the scope of LASI - Intelligent Systems Associate Laboratory, reference LA/P/0104/2020, financed by national funds under the Multi‑Year Funding Program for R&D Units
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the attribution of one (1) research grant within the scope of LASI - Intelligent Systems Associate Laboratory, reference LA/P/0104/2020, financed by national funds under the Multi‑Year Funding Program for R&D Units
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environmental impact. By drawing on interdisciplinary expertise (spanning renewable energy engineering, power systems and energy market integration, stochastic multi-objective optimization, and data‐driven