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to develop generative AI methods for nanoparticle drug delivery design, at the intersection of machine learning, explainability, and pharmaceutical nanotechnology. Job description We are looking for a
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, PlasmaObs, LCRS, Moonlight and Henon. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of activity/research for the traineeship Many challenges and trends will affect the operations
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models that provide evidence-based reasoning for mission-critical decisions. Explainable AI for mission-critical decision support: design interpretable machine learning architectures capable of offering
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outcomes under different market design scenarios. The research will combine machine learning, stochastic optimization, and agent-based modelling with behavioural experiments. Case studies from emerging
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. Background: You hold a PhD in Computer Science, Machine Learning, Electrical Engineering, Embedded Systems or related fields. Core Expertise: Strong expertise in Federated Learning and/or Continual Learning
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19 Dec 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Computer engineering Engineering » Systems engineering Researcher Profile
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engineering Engineering » Systems engineering Ethics in social sciences Researcher Profile Recognised Researcher (R2) Country Netherlands Application Deadline 26 Jan 2026 - 22:59 (UTC) Type of Contract
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at the intersection of military readiness and corporate operations. Defence capability development in Europe and European defence industry. Conduct independent empirically driven and comparative case-study focused
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route to produce high-quality recyclates, but current implementations rely on static process design and control that don’t account for feedstock variability, inefficient solvent use, and high energy
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Observation Programmes. You will be part of the ESA Φ-lab. Our mission is to accelerate the future of Earth Observation (EO) by embracing disruptive innovation and serving as the catalyst for disruptive and