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- Institute of Photonic Sciences
- ICFO - The Institute of Photonic Sciences
- Universitat Autònoma de Barcelona
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- Achucarro Basque Center for Neuroscience
- BC3 - Basque Centre for Climate Change
- Barcelona Supercomputing Center (BSC)
- CRAG-Centre de Recerca Agrigenòmica
- Centre de Recerca en Agrigenòmica
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- Institut de Físiques d'Altes Energies (IFAE)
- Institute for bioengineering of Catalonia, IBEC
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track record of work on quantum cryptography and quantum information theory.. LanguagesENGLISHLevelExcellent Additional Information Benefits ICFO is an equal opportunity employer. Candidates are selected
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assessments Where to apply Website https://sl1nk.com/lKt56 Requirements Research FieldNeurosciencesEducation LevelPhD or equivalent Skills/Qualifications PhD in Biomedicine, or a related field. Proven track
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: Define and track metrics (MAE on Hamiltonian elements, band-structure error, DOS overlap, transport-relevant figures); compare against classical parameterisations. Uncertainty and active learning
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(ImageJ/Fiji) · GBM biology knowledge · Experience of supervising student research projects · Evidence of a developing track record in publishing and dissemination of high-quality publications in peer
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presentations. * Desirable: * Prior experience with Alzheimer s disease models and glia/astrocyte biology. * Prior track record of peer-reviewed publications in relevant fields. * Prior experience supervising
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an advantage. Experience working with model or non-model plant species. Proven track record of publications in relevant areas. Skills: Strong experimental and analytical skills in molecular biology and plant
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for quantitative microscopy data. - Proven track record of peer-reviewed scientific publications - Experience in web application development. - Ability to work independently and proactively, with strong project
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methodologies will also be highly valued. We seek candidates with at least 3 years after their PhD, with a track record of research publications in high quality international academic journals and press, and with
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., evolutionary algorithms/strategies, mixed-integer search, multi-objective methods). Strong Python and scientific-computing skills (data handling, experiment tracking, testing, version control). Practical
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: Define and track metrics (MAE on Hamiltonian elements, band-structure error, DOS overlap, transport-relevant figures); compare against classical parameterisations. Uncertainty and active learning