19 phd-position-for-fully-funded-reserch-in-computer-vision Postdoctoral positions at ICN2
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at its facilities in Bellaterra (Barcelona), Spain as part of the AuSpire researcher training program, co-funded by the European Commission under the MSCA COFUND scheme. The total working hours per week
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areas of nanoscience and nanotechnology. Job title: Postodoctoral Researcher Position in (Scanning) Transmission Electron Microscopy of Catalytic Materials for Green Hydrogen and Energy Applications
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tools. Requirements: Education: · Undergraduate in Physics, Chemistry, Materials Science, or related disciplines. · PhD in Physics, Materials Science, Chemistry, Computer Science, or related disciplines
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environment Estimated Incorporation date: January 2026 Funded by Reticular enzyme-like catalysis (RETICAT)- BBVA Foundation Fundamentos Program 2024 How to apply: All applications must be made via the ICN2
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confocal microscopy) and flow cytometry. The Postdoctoral Researcher will be expected to interact effectively with researchers from a range of different disciplines to contribute to the programme of research
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internal reports and manuscripts. Requirements: Minimum (required) PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related. Solid knowledge molecular dynamics
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Funded by the European Research Council (ERC) in the framework of the H2020 Research and Innovation Programme (ERC AdG; GA 101019003 CLIPOFF-CHEM) How to apply: All applications must be made via the ICN2
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benchmarking. Contribution to SIESTA training events. Contribution to other activities in the group. Requirements: PhD in Physics, Materials Science, Chemistry, Computer Science, or related disciplines
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: Education: PhD within the field of electrochemistry. Knowledge andProfessional Experience: Experience in electrocatalysis and scanning tunnelling microscopy (STM) Relevant publications within STM and
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. Requirements: Minimum: PhD in Physics, Materials Science, Computational Science/Engineering, Computer Science, or related field. Demonstrated experience implementing heuristic/metaheuristic optimisation (e.g