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and artistic research outputs excellent oral and written communication skills demonstrated experience in collaborative processes with demonstrated ability to work independently and as part of a team
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Job description Computation-in-Memory (CIM) is being investigated for energy-efficient artificial intelligence (AI) applications. However, this new computing paradigm faces various design challenges
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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twins are leveraged to develop paradigm shifts in quality assurance, quality control, real-time process control, and design optimization for the United States. In this digital environment, you will use
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Postdoctoral Research Associate in Sum-Frequency Generation Microscopy of Biomolecular Self-Assembly
the institute focusses on the structure and dynamics of elementary processes in solids and at surfaces. Within this broader research theme, the Nonlinear Chemical Imaging (NCI) group of Dr. Alexander Fellows
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with skills in computation and image processing is highly desired. Excellent communication skills and an ability to work across platforms in a collaborative style are desired. St. Jude is an Equal
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technologies on the vacuum Space Coronagraph Optical Bench (SCoOB), coronagraphic image post-processing for existing and future space telescopes, simulation of coronagraphs for future missions including
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13 Sep 2025 Job Information Organisation/Company Linnaeus University Research Field Computer science » Computer systems Researcher Profile Recognised Researcher (R2) Country Sweden Application
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have experience in routine molecular biology techniques like Western blotting, PCR, immunohistochemistry and/or microscopy. Experience with electrophysiology or live-cell imaging techniques like calcium
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics