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in a strongly heterogeneous setting (e.g., CPUs+GPUs). Additionally, this work can benefit from the developments of WP1 and WP2 of Exa-SofT around the development of optimization techniques
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the research team in the area of Swarm Intelligence, Reinforcement Learning and Optimization Techniques. As a Postdoctoral researcher, you will: Lead cutting edge research in Swarm Intelligence and Machine
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, safety, and compliance. Perform preventive maintenance on laboratory equipment to keep them in optimal working condition. Conduct experiments related to identifying metabolites in plant and biological
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(at least 3 months). Experience in development and optimization of lipid nanoparticles. Experience in cell cultures and nanoparticle assays. Experience in in vitro models of ocular tolerance. Experience in in
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community. Main Tasks and responsibilities: Collaborate with theoretical and experimental partners to design and characterize optimized altermagnetic devices for information processing. Fabricate nanodevices
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optimally interact with a varied population of diverse audiences. We are looking for someone who shares our values and who will support the mission of the university through their work. Qualifications: PhD in
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of the corresponding manufacturing processes. The selected candidate will be responsible for: Leading the formulation development of the solid diagnostic product. Designing and optimizing the manufacturing process
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an assessment framework that will enable us to better identify and propose, in a transparent manner, management measures for optimal sustainability, tailored to each study area and applicable to different sites
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experimental design and analytical method optimization, training others in laboratory skills and analytical chemistry, and strong writing and communication skills. Applications, including a cover letter and a
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optimization of tailor-made endolysin variants using modern bioinformatic methods and tools. What you contribute General university entrance qualification Doctorate Very good English skills Knowledge of common