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Testing and Experimentation Facility (TEF) for the energy field. Specifically, it leverages AI and cutting-edge infrastructure to optimize EV charging and energy systems. By integrating distributed energy
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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Postdoc in Genetic Engineering of Green Microalga Chlamydomonas Reinhardtii with the Purpose of A...
. Recent studies identified natural bio-converters, such as bacteria and fungi that contain efficient PET-degrading enzymes (PETases). These PETases are currently being optimized to enhance their enzymatic
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techniques. Preferred Qualifications: · Demonstrated ability in the design and optimization of synthetic strategies and approaches for the production of lipids and/or polymers · Proficiency with the analytical
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(EKFZ: https://ekfz.uni-goettingen.de) Your tasks Large-scale and in-depth characterization of optimized Channelrhodopsin variants for basic research in neuroscience and future optogenetic therapies
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translation to therapy. The University of Miami Miller School of Medicine and the Sylvester Comprehensive Cancer Center are an optimal environment for career growth. The Department of Molecular & Cellular
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to world-class facilities and equipment. Key Responsibilities: Formulate and optimize nanoparticle platforms using techniques such as microfluidics, extrusion, and self-assembly. Perform comprehensive
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design, fabricate, and test high efficiency superconducting nanowire single-photon detectors (SNSPDs) and detector arrays optimized for mid-infrared spectroscopy. The goal of this work is to develop both
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, CT, and other imaging techniques. Design and optimize multiparametric models to analyze complex imaging datasets and extract clinically relevant features. Develop and optimize newer clinically relevant
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., VAEs, GANs, transformer-based models) to large-scale biomedical and biological data, including developing and optimizing models to predict disease progression and create realistic patient profiles