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ARIADNE – an interdisciplinary research project developing a screening tool to support clinical evaluation for psychosis risk, powered by generative artificial intelligence. You will lead a project to
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of resistive switching mechanisms in meta/insulator/metal memristive materials Qualifications • PhD in Computational and Applied Physics • Proficiency using software for the simulation of atomic structure
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years. The project involves the synthesis and characterisation of molecular lanthanide complexes to develop physical inorganic principles for controlling optical linewidths and oscillator strengths in
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$59,000/year Type of Position Staff Position Time Status Full-Time Required Education PhD/MD-PhD Required Related Experience Immunology Required License/Registration/Certification None Physical Requirements
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& Human Flourishing, Stoke House, Oxford, OX3 9BX. You will lead a programme of research in the foundations of AI alignment for human flourishing.You will manage and monitor research resources and
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Postdoctoral position for the project Human AI Collaboration: Imaginaries, Interventions, Interfaces
the stated framework of the research project (max. 1-2 pages). Please note that although the application process can be completed on the Aarhus University system without uploading publications or a teaching
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systems. Spectroscopy, hyperspectral imaging, remote sensing, IoT, and process measurements are important data sources within this broader framework rather than requirements defining a single experimental
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check may form part of the selection process. Project: Youth climate Justice project For an information package including full details of the post, selection criteria and application process see https
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Postdoctoral Associate Required Qualifications (as evidenced by an attached resume): Doctoral Degree (or foreign equivalent) in Chemistry, Physics, Chemical Physics, Nanoscience and Technology, or a
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/benefits-overview . Posting Summary Seeking a highly motivated Postdoctoral Associate to lead research working in quantitative ecology, using big datasets (e.g. GBIF, eBird, Movebank), remote sensing data