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of development. You are motivated to develop and optimize cutting edge single cell ribosome profiling techniques and you have affinity with bioinformatics. We are looking for a colleague that meets the following
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led by Prof. Marie Schölmerich at the Department of Environmental Systems Science, ETH Zurich, invites applications for a fully funded PhD position. Our group explores the fascinating world of anaerobic
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system. The project is supervised by Prof. Hannah Dugdale (University of Groningen), Prof. David S. Richardson (University of East Anglia, UK) and Prof. Kees van Oers (Netherlands Institute of Ecology
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patients. The candidate will work closely with a multidisciplinary team consisting of colleagues from biomedical sciences, medicine, bioinformatics, and statistics, both within and outside UMC Utrecht
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(chaired by Prof. Niklas Wahlberg, Lund University, Sweden; https://10klepgenomes.eu/ ) and close collaborators in this project include Prof. Mark Blaxter and Dr. Joana Meier (Wellcome Sanger Institute, UK
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, machine learning, bioinformatics, AI, or a related field. Strong background in machine learning and data analysis. Interest in single-cell omics, spatial data, or systems neuroscience. Intellectual
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PhD Student Brain multiregion singlecell transcriptomics of Myalgic Encephalomyelitis/CFSyndrome NIN
candidate who is eager to unravel complex disease mechanisms. You have: A Master’s degree in neuroscience, bioinformatics, biomedical sciences, or a related field. A strong interest in transcriptomics, brain
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-on training and mobility will be available. Our research team is part of the 10kLepGenomes COST Action (chaired by Prof. Niklas Wahlberg, Lund University, Sweden; https://10klepgenomes.eu/ ) and close
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-motivation, flexibility and team spirit. Experience with techniques such as cell culture, CAM model, qRT-PCR, fluorescence microscopy and/or bioinformatics would be a plus. Your teaching competences are in
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supervised by Prof. Dr. Suzan Verberne and Dr. Niki van Stein at the Leiden Institute of Advanced Computer Science (LIACS), Leiden University. The focus is on explainability for multimodal foundation models