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for the European Higher Education Area ) in pharmacy, chemistry or a similar subject and a minimum of 4 years’ professional experience in a similar role (e.g. developing and/or maintaining stakeholder engagement
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. Successful candidates should have an ongoing research and publication program and teaching experience. In addition to research and teaching, responsibilities include service to the Department and the
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reproducible scale-up protocols and develop standard operating procedures. Support multiple projects within the group requiring scale-up and contribute to cross-functional teams. Interface with external partners
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Virtual laboratory to predict the ability of a fluctuating biomass to satisfy a material use-VARIOUS
Work environment, missions and activities Nature and purpose of the research project to be developed and related activities. Industries are having to reduce emissions resulting in the need to revamp
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transport regimes, with a focus on the exploration of inhouse developed materials, and on exploring nonlinear magnonic processes triggered by microwave and spin-orbit torque excitations. The recruited person
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impact A demonstrated commitment to mentoring and fostering the next generation of researchers Willingness to contribute to teaching programmes at the undergraduate and graduate levels in areas related
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) — to join our team. You will be directly involved in developing and optimizing ion beam processes to improve device performance in MRAM and magnetic sensor applications. Beyond R&D, we are looking for a
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; Participate in lab meetings and scientific discussions. Key Skills, Experience & Qualifications Education & Experience: Enrolled in a Master’s programme (M2) in biology, immunology, oncology, or a closely
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the European Testing and Experimentation Facility (TEF) for AI and Robotics in Smart Cities and Communities. With 15 test sites across the EU, it supports companies and public actors in developing
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redefinition of behavioral features or pose challenges in their detection. The projects To address these challenges, we propose developing a Bayesian Program Synthesis (BPS) methodology for generating synthetic