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to) SIESTA (www.siesta-project.org) and its TranSIESTA functionality. SIESTA is a multi-purpose first-principles method and program, based on Density Functional Theory, which can be used to describe the atomic
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(Wash. U. St Louis, UT Southwestern), Italy (Milan, Padova) and locally with INEFC. They will be in charge of the devleopment of the next generation SCOS systems including novel approaches to new sources
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advantages contracting some products (health insurance, childcare, training, among others.) Training activities: languages, mentoring programme, wellbeing programme. International environment Estimated
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opportunity for the successful candidates to pursue a career in the field of virology or immunology. Required Qualifications A PhD degree in microbiology, immunology or related field. Strong written and oral communication
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Build a tool to obtain periodic
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to large datasets You have proven programming competence in Python and/or R, and expertise in Linux and high-performance computing environments You have a genuine interest in, and prior exposure (through lab
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. Experience with MBE equipment and synthesis would be a bonus. Giv-en the specificity of this position, preference will be given to bilingual candidates, fluent in both English and Chinese. Appointment Details
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-time Hours Per Week 37,5 Offer Starting Date 1 Oct 2025 Is the job funded through the EU Research Framework Programme? Horizon 2020 Reference Number ERC-Stg. 758885 Is the Job related to staff position
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, the Spanish Ministry of Science and Innovation, Generalitat de Catalunya, an AXA chair, European Foundation for the Study of Diabetes, the Marie Skłodowska-Curie Actions program, and a CIBERDEM diabetes network
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the EU Research Framework Programme? Horizon Europe - MSCA Is the Job related to staff position within a Research Infrastructure? No Offer Description Advanced rock mass characterization with MWD and image