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by two mentors within the SPACER project, and will have multiple opportunities to participate in professional and personal development training. Through her/his work she/he will gain a unique skill-set
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Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth
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spatial omics datasets. The position will also contribute to multi-modal data integration efforts that combine imaging, genomics, and machine learning approaches. Key Responsibilities Data Processing
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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, biology, engineering, machine learning / data science, coding. How to apply: This is an Expression of Interest process. To express your interest in applying, candidates must supply the following information
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need to be enrolled in one of the EPFL doctoral school programs. This is a separate application process that you can start in parallel. We suggest that you apply to the Doctoral Program in Mechanics
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(bio-)chemistry, physics, and engineering expertise to study molecules and cells, taking advantage of optical and single-molecule imaging, molecular probes, molecular biology, and 'large' data analysis
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development and marine management. Your primary tasks will be to: Compile and harmonize data from multiple sources (e.g., EMODnet, Copernicus, fisheries surveys, citizen science). Engage with data managers and
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of transmission electron microscopes and/or scanning electron microscopes Knowledge of artificial intelligence and machine learning and their applications in electron microscopy Knowledge of computer programming
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. ✔ Close supervision by leading experts in bioelectroanalysis: 250+ publications (85% in Q1, 80% in D1 journals) 5 international patents Multiple technology-based startups ✔ Multidisciplinary research