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Mineral Residues: Comprehensive Characterization and Advanced Material Applications Hosting: Tallinn University of Technology, secondment: The University of Eastern Finland (FI) Supervisory team: Dr. Birgit
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for sustainable production of food by applying your microengineering and material science skills? Here, we can offer you a unique opportunity to do exactly that in a dynamic research environment. In the SOLARSPOON
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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon
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Job Description The Quantum Physics & Information Technology (QPIT) group at DTU Physics is seeking exceptional individuals for PhD positions in quantum sensing using color centers in diamond. Our
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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AIPhD in computational modelling RAM³ is a WASP-WISE NEST project This recruitment is connected to the Wallenberg Initiative Materials Science for Sustainability All early-stage researchers recruited
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Phenomena , Cold Atom Physics , Cold Atoms and Molecules , Cold QCD Group , collider physics , Collinear Fast Beam Laser Spectroscopy , Complex Quantum Systems , Computational Materials Sciences
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(or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable. Project key words Retinal imaging, data-analytics, computer vision, big data Funding The studentship, funded by