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(R1) Positions PhD Positions Country Spain Application Deadline 29 Oct 2025 - 23:59 (Europe/Amsterdam) Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Offer Starting Date 1 Jan 2026
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technologists to push strategies into production What we're looking for PhDs graduating by Summer 2026 or postdocs in quantitative fields such as Mathematics, Physics, Statistics, Electrical Engineering, Computer
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(R1) Positions PhD Positions Country Spain Application Deadline 29 Oct 2025 - 23:59 (Europe/Lisbon) Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Offer Starting Date 1 Jan 2026 Is
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Predoctoral researcher at the Targeted Therapeutics & Nanodevices Research Group (Project BRAINZYME)
(R1) Positions PhD Positions Country Spain Application Deadline 29 Oct 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Offer Starting Date 1 Jan 2026 Is
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(R1) Positions PhD Positions Country Spain Application Deadline 29 Oct 2025 - 23:59 (Europe/Amsterdam) Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Offer Starting Date 1 Jan 2026
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articles at the maximum level possible. Present the research in scientific conferences and other forums. Supervise undergraduate, Master and PhD students in agreement with the group leader. Be
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equality, inclusion and diversity (EDI) in line with Newcastle University’s EDI principles Qualifications Research Assistant First degree in engineering or numerate subject (e.g., mathematics, physical
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at international scientific conferences and other forums. Supervise undergraduate, Master’s, PhD students and postdoctoral researchers in agreement with the group leader. Act as responsible and contact person when
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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees