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who thrives in a collaborative and interdisciplinary research environment. The ideal candidate possesses a PhD degree in chemistry or chemical engineering, materials science, physics, or related
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. Required PhD in Computer Science / AI / Machine Learning Strong publication record in AI, ML systems, or related areas Strong programming skills in Python, C/C++ and experience with PyTorch, TensorFlow, JAX
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relevance Profile Interested candidates should meet the following requirements to be eligible for the position: A PhD or Doctoral degree in Energy Systems, Computer Science, Applied Mathematics, or a field
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pipelines to support the labs long-term research interests Proactively manage the labs genomic data resources Supervise and mentor PhD and Masters students in comparative fungal genomics Assist in
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documents: CV with list of publications A one page summary of your PhD (up to 3,500 characters) A two page presentation of your research plans during your time in the professorship (up to 7,000 characters
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: Experience with analyzing GPS tracks Good data-handling skills and ability to use R (compulsary) and preferably also Python and/or GIS competently Statistical/causal inference knowledge PhD degree in a related
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apply at https://careers.epfl.ch/job/Lausanne-Postdoctoral-Position-in-Stochastic-Analysis/1163749755/ . Contact: Bernadette Brun, + 41 21 693 9051 Email: Postal Mail: EPFL SB MATH STOAN MA C2 647
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evaluation. Collaborating with heritage partners (e.g., Swiss National Museum, SIK-ISEA) and preparing evaluation reports and a white paper for applied use. PhD in Digital Humanities, Imaging Science, Computer
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of electronic devices has a long and successful history of accompanying experimental developments, be it for transistors or memory cells. Nowadays, to be of practical relevance, such technology computer aided
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 2 months ago
(RuzicaDadic), University of Fribourg (Martina Barandun and Horst Machguth), and ETHZurich (Evan Miles). The core team consists of the 4 PIs, 4 PhD students, and 4 Postdocsand aims to quantify the impact of