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(SNSF) and is a collaboration between LESE and groups from the Chemistry department of ETH Zürich (Prof. Christophe Copéret group), University of Zurich (Dr. Iannuzzi group) and the Paul Scherrer
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analyze the data. Your task will be to correlate biomarkers derived from rTMS and NIRI with clinical outcomes, in order to personalize stroke rehabilitation and improve the recovery process. Statistical
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international experts in machine learning, seismic monitoring/imaging, statistical seismology, and geomechanical modelling. Project team members include Dr. Federica Lanza (ETH Zürich), Dr. Luigi Passarelli (INGV
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, computer science, or related fields. This includes, but is not limited to, psychology, mathematics, engineering, physics, or statistics. Geographical Eligibility: We are seeking candidates who are currently
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bioinformatics, statistics, and programming The candidate must have a strong motivation and interest in collaboration with multi-disciplinary scientists. They must be able to communicate effectively in a highly
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science, statistics, applied mathematics, or related fields Proficiency in developing and deploying machine learning models (e.g., using Python, R) Experience in data wrangling and feature engineering
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culture, and flow cytometry preparation of deep sequencing libraries for functional genomics experiments bioinformatics, statistics, and programming The candidate must have a strong motivation and interest
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, statistical mechanics, Monte Carlo modelling is an advantage Your workplace Your workplace We offer ETH Zurich is a family-friendly employer with excellent wokring conditions. You can look forward