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with nanoparticle synthesis and characterization • Strong skills in cell culture and basic molecular biology Preferred Qualifications • Experience designing and optimizing synthetic routes for lipids and
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professional groups work hand in hand to provide our patients with optimal treatment. PhD position / Postdoc position (m/f/d) in Cancer Genomics and Oncogenic Signaling Full- or part-time | temporary (12 month
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processes and/or optimization. Specific experience with sampling methods for Bayesian is highly appreciated. Experience with cardiac electrophysiological modeling is a plus. Candidates should have experience
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, execution, and evaluation of experimental series as well as process optimization Presentation and publication of results and communication with project partners Project management, acquisition of new topics
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
images, including Positron Emission Tomography, temporal multi-modal MRI and Histology, which we use for models training and validation. Objectives A key research focus of our group is the optimization
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(training provided). Design and optimize protocols for new biophysical assays to address complex cancer biology questions.– Example project: Science, 2023 Writing and submitting NIH training grants, including
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, and optimize biomass pyrolysis/gasification reactors for clean energy production. Process Optimization: Investigate reactor parameters, feedstock behavior, and thermodynamics to enhance yield
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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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specific transcription factors using targeted mRNA delivery technologies, with the vision of enhancing responsiveness to immune checkpoint inhibitors. Key Responsibilities: Design, execute, and optimize
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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