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, C++, or equivalent) Experience with 3D modelling, rendering, or fabrication, and haptic feedback Familiarity with computational or optimization methods applied to interaction (e.g., computational UI
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strategies. About You You will hold a PhD in Materials Science, Nanotechnology, Applied Physics, Electrical Engineering, or a related discipline. You will have experience in 3D metamaterials or architected
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metadata (location, climate, soil properties) into the GlobalSoilMacrofauna format. Deposit datasets in open-access cloud/local repositories. Data Analysis– Explore drivers of macrofauna abundance/diversity
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experiments, and connect them into live experimental campaigns so that AI checks every candidate before it reaches the robot deployed on the Genesis American Science Cloud with the Materials Project as
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
desire to learn new (technical) skills; and proficiency with Python, Javascript, XML, CSS, and LaTeX. PREFERRED: Experience creating plots and 3D interactive images in Mathematica, MATLAB, or python; ties
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antigens presented by MHC molecules. This curiosity-driven project develops cutting-edge AI technology for 3D TCR–pMHC modeling to improve neoantigen identification, TCR specificity prediction, and TCR
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set of synthetic and spectroscopic tools that connect molecular structure and organization, their properties and function. This is what you are going to do Design and build flow setups using 3D printer
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Post Doctoral Researcher Rinn Artificial Intelligence – Research & Innovation in Data Science and AI
translational statistics. Depending on their profile, the successful candidate will work on one of the following strands. • Bespoke modelling of tumour metabolic function using 3D and 4D imaging data • Cancer
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what you are going to do Design and build flow setups using 3D printer, pumps, valves operated by a computer and the corresponding software Develop flow cells to connect various spectroscopic tools
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-cloud robotic control at our Garmisch-Partenkirchen campus. The project investigates how advanced robotic control and AI-assisted teleoperation can be safely deployed over communication networks with