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26 Feb 2026 Job Information Organisation/Company Soluciones Agricolas Ecoinnovadoras SL Research Field All Researcher Profile Recognised Researcher (R2) Positions PhD Positions Application Deadline
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electrocatalysts. Main Tasks and responsibilities: The PhD position is framed within the MAIAMI project. The student will work on DFT and molecular dynamics simulations, generating structural and electronic
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implementations and valuable chemical transformations. However, due to the reactive nature of radicals and the non-trivial chemistry required for their preparation, strict structural and electronic limitations
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Administrative Region. HKUST(GZ) is situated in the center of the Guangdong-Hong Kong-Macau Greater Bay Area, one of the most vibrant and dynamic regions in the world, and the establishment and development
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and outreach. Co-supervision of PhD students, MSc and/or exchange students. Active contribution to group meetings and discussions. Share this opening! Use the following URL: https://jobs.icfo.eu/?detail
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). Creativity, problem-solving ability, and interest in applying structural engineering to emerging construction technologies. Specific Requirements PhD degree is mandatory and must be completed at the time of
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molecules. Characterise the structure and photophysical and photochemical properties of nanostructured assemblies using static and time-resolved spectroscopic techniques (including X-ray techniques). Support
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 2 months ago
PhD degree. - Integration into a well-established and dynamic research group with active projects in breast cancer, colon cancer and lymphoma. - Supervision by experienced researchers:Dr. Pablo Conesa
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) Positions PhD Positions Application Deadline 11 Feb 2026 - 23:59 (Europe/Madrid) Country Spain Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme
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hardware constraints, improve system control, and unlock new modes of problem-solving that surpass classical approaches. The ML-QSIM project is built upon a robust multi-node and multi-regional structure