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papers. Requirements: Education: PhD in Physics or related degree Knowledge: Complex oxides (Ferroelectrics, antiferroelectric, nickelates, etc), nanomechanics, photovoltaics, scanning force microscopy
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projects and technical leadership. Basic Qualifications: Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related technical field. Proven experience in
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. The candidate will provide guidance and support to MSc and PhD students, assisting in the supervision and training of junior researchers in areas such as device fabrication, biosensor assembly, and
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meeting and participating to annual project meetings. The candidate will provide guidance and support to MSc and PhD students, assisting in the supervision and training of junior researchers in areas
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plus Education and training PhD in Bioinformatics or in Biology, Machine Learning, Statistics, Physics, Mathematics, Chemistry or related areas Languages: Highly proficient in both spoken and written
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ICFO offers a limited number of PhD positions to well-qualified applicants who wish to obtain a doctoral degree in any of the research topics available within our Research Groups . Our PhD-program
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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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Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related technical field. A strong publication record, with first-author papers
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ICFO offers PhD-fellowship positions to well-qualified graduate students, who wish to obtain a doctoral degree in any of the research topics covered at ICFO. Our PhD-program brings together top
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areas of nanoscience and nanotechnology. Job Title: PhD student - Inorganic Nanoparticles Group Research area or group: Inorganic Nanoparticles Group Description of Group/Project: The Inorganic