46 experience-design-"https:"-"https:"-"https:"-"https:"-";" Postdoctoral positions in Switzerland
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studies. We expect a strong scientific background and proven track record in accelerator physics, physics-based simulations, numerical optimization and computational design. Experience with modular and
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6,500 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more
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responsibility for your own research Provide mentorship on chemical synthesis and characterization Research in close collaboration with other lab members and international collaborators Experiment design and
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an interdisciplinary team. Your tasks Conduct physical vapor deposition experiments using advanced PVD processes such as synchronized HiPIMS Perform in-depth materials characterization and surface analysis Apply and
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-loop drug discovery. The project aims to establish an integrated Design–Make–Test–Analyze (DMTA) platform combining generative AI, ultra-large synthetically accessible chemical spaces, physics-informed
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informatics, collaborating in an interdisciplinary team. Postdoctoral Researcher in the Development of Thin Films and Deposition Processes using Artificial Intelligence and Autonomous Experiments. Your tasks
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoc in ML-Based Co-Design at EPFL Mission The EPFL computer vision lab (https://www.epfl.ch
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are important for young and ambitious group. In return, you get to design your own experiences! Enjoy collaborations with various other scientific groups, take on a leading role in international teams. We offer A
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of materials, interfaces and manufacturing processes relevant to PV modules. Experience in material characterization and quantitative analysis of experimental data. Ability to independently define, plan and
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project. The goal is to find out, through concrete experiments, where these approaches help in the design and analysis of numerical schemes for PDEs, and where they still fall short. What you will do As a