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on established expertise in nanoparticle synthesis and surface chemistry, this project will optimize nanomaterial design for circulation, targeting, and therapeutic performance in neuroblastoma organoids, enabling
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tools for LAttice Structures» , funded by the Swiss National Science Foundation, we are opening a postdoctoral position for developing efficient algorithms for the topology optimization of architected
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creation of decarbonized, resilient, and equitable energy systems. This PostDoc position is offered in collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL ( Prof
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system serving as a real-world lead-optimization case study. The successful candidate will play a central role in the computational and AI components of the project and work closely with our international
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. As part of a multidisciplinary team of academic and industrial researchers, you will contribute to the development and optimization of next-generation fabrication technologies with direct relevance
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will closely interact with experts in microfluidics and bioinformatics, while spearheading the above project. Main duties and responsibilities include Optimization of single-cell sequencing workflows
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cutting-edge research in the fields of matter and materials, energy and environment and human health. By performing fundamental and applied research, we work on sustainable solutions for major challenges
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the ability to harness and optimize massive computational resources. However, this rapid growth in computational demands comes with a critical challenge: energy limitations. Around the globe, new power plants
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develop novel learning-based control and policy optimization techniques. We're looking for a skilled machine learning (ML) engineer to develop cutting-edge AI algorithms for digital twin applications in
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. The performance of such batteries hinges on the solid booster formulation, morphology, and the efficiency of charge transfer between mediator and solid under continuous flow. Your tasks Your task is to develop