139 phd-computational-"IMPRS-ML"-"IMPRS-ML"-"IMPRS-ML" positions at ETH Zurich in Switzerland
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Required experience: CH/EU/EFTA citizenship or a valid work permit for Switzerland A Master’s degree (ETH, university) in engineering, computer science, or a related field Strong academic performance meeting
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at the Department of Biosystems Science and Engineering (D-BSSE) of the ETH Zurich in Basel invites exceptional candidates to apply for PhD and postdoctoral positions in pioneering projects developing synthetic
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master’s degree preferably in Computer Science, Information Technology, Information Systems, Statistics, Data Science, Engineering, or a related field Strong machine learning and programming experience with
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of SIS (e.g., HPC systems engineers, data scientists, research software developers) and external collaborators. Profile a PhD or equivalent in Computational or Computer Science, Engineering, Physics, or a
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founded by Innosuisse and the project is in close collaboration with an industrial partner. Profile Applicants for the position are expected to have earned a PhD in heterogeneous catalysis with documented
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technologies to characterize animal genomes, and apply bioinformatics and statistical genomics approaches to identify trait-associated sequence variation. We offer a PhD position at the interface
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students conduct in the department. Profile The ideal candidate will possess: A PhD in electrical engineering, biomedical engineering, computer science, or a related discipline, Experience in the analysis
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) at ETH Zürich within the Centre for Digital Health Interventions . You will lead the Revelio initiative and co-supervise two PhD students in close collaboration with Prof. Elgar Fleisch (ETH Zürich) and
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, documentation, and experimental implementation Profile PhD in Mechatronics, Robotics, Electronics, or related engineering areas Proficiency in mechanical design, embedded systems, and hardware-software
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broader research agenda focused on how digital infrastructure and computational tools can support (or hinder) progress toward effective, coordinated, and equitable biodiversity governance. Research topics