173 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"SciLifeLab" positions at ETH Zurich in Switzerland
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The primary focus of this position is the project-specific analyses of diverse high-throughput multi-omics datasets, encompassing a broad range of data types such as whole-genome and transcriptome
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exclusively accept applications submitted through this online application portal. Applications via email or postal services will not be considered. Further information about Tethys Robotics can be found on our
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will begin on 23 February until the position is filled. Further information about the Planetary Geochemistry group can be found here . Questions regarding the position should be directed to Prof. Maria
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models or glioblastoma research Familiarity with transcriptomic methods (RNA-seq, FISH, spatial transcriptomics) Programming skills for data analysis (Python, R, or MATLAB) Workplace Workplace We offer
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application with the following documents: Motivation letter (max 1 page) Detailed CV Transcripts of all degrees including ranking information (English) Names and contact information of at least three references
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80%, Zurich, fixed-term The Biomedical Data Science (BMDS) Lab investigates data-driven solutions for healthcare applications with a focus on neurological conditions such as spinal cord injury (SCI
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problems in scientific or engineering domains using proprietary/real data (beyond public benchmarks), where challenges like distributional generalization, multi-objective trade-offs, causality, privacy
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services will not be considered. Further information about LESE can be found on our website . Questions regarding these positions should be directed to Dr. Paula Abdala: abdalap@ethz.ch or Prof. Christoph
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, engineering, physics, or a related field, and with strong interest in the cryosphere. The successful candidate has experience in computational data analysis or numerical modelling. You are eager to work
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frames). Project background The work focuses on data-driven generation of structural systems. You will be involved in developing, experimenting with, and evaluating machine learning models that help