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? With data-driven methods, new opportunities arise to understand ecosystems as complex, dynamic networks. This project aims to analyse the world’s most extensive eDNA database, consisting of weekly
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or LibreOffice, Linux proficient in dealing with operating systems and high-performance computing facilities We expect: the ability to work independently and on your own initiative a methodical and systematic
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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to protein engineering and molecular cloning, Experienced in bioinformatic genome analysis and computational tools related to protein structure analysis and prediction, Sufficient expertise in standard
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biochemistry to join a newly funded GPCR collaborative project to investigate the structural dynamics of GPCRs and their signaling partners using biophysical methods, including single-molecule FRET (smFRET
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health. HT is composed of five Centres: Neurogenomics, Computational Biology, Structural Biology, Genomics, and Health Data Science. The Centres work together to enable interdisciplinary research and to
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in basic cellular and immunological methods, including multi-color flow cytometry, ELISA, cell killing assays, experience with analysis of human samples, and extensive experience with mouse cancer
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partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments
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Pneumatic Tires, Structure-Process-Properties Relationships. How will you contribute? Do you have proven skills in data analysis, machine learning, as well as in mathematical and computational modelling? You
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advanced data-driven methods and have the autonomy to set your own scientific emphasis. As team member of the ERC Starting Grant “MesoClou”, you will work with PhD students and a fellow postdoc and be