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of Twente and will be (co-)supervised by dr. Ying Wang, prof. dr. Johannes H. Hegeman and prof. dr. ir. Peter H. Veltink. The candidate will closely collaborate with dr. Ying Wang and fellow team members and
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experience Knowledge of electrochemistry and corrosion English language: Good level of English How to apply: submit application package (see below) to Prof. Fátima Montmeor (mfmontemor@tecnico.ulisboa.pt
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, the Chair of Ultrafast Microscopy and Photonics (Prof. Alexey Chernikov) offers, subject to the availability of resources, a position as Research Associate / PhD Student (m/f/x) (subject to personal
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of Ultrafast Microscopy and Photonics (Prof. Alexey Chernikov) offers, subject to the availability of resources, a position as Research Associate / PhD Student (m/f/x) (subject to personal qualification
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to compensate for such aberrations, significantly enhancing image quality. Adaptive requires knowledge of the wavefront to be corrected. Our team has been developing a machine-learning approach to wavefront
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The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences | Poland | 4 days ago
. The project will be realised in a vibrant and internationally recognised group led by Prof. Agnieszka Chacińska (https://imol.institute/leaders/chacinska-group/ ) We are looking for a highly motivated person to
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efforts; amplify Indigenous and community voices; and shape policies that are not only effective, but just and inclusive. By bridging knowledge systems and fostering creative public engagement, HASS
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. The PhD is supervised by Prof. Chiel Poffé (principal supervisor) and Prof. Evelien Van Roie (co-supervisor). This PhD is done in close collaboration with rehabilitation centers and you can use a new
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics