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- and wet-lab methods. We combine cutting-edge basic science with strong ties to the clinic and aim to directly influence future clinical practice. The doctoral student project and the duties
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and numerical modelling of natural clays at both laboratory and field scale. We are active members of the ALERT Geomaterials network and other international committees. Our diverse and international
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atmosphere. The mid-sized city (100,000 inhabitants) provides affordable housing, numerous cafés and restaurants, excellent sports and cultural facilities, and easy access to scenic nature reserves, hiking
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these questions through an interdisciplinary lens, with a strong focus on mathematical and computational methods closely connected to evolutionary theory and biological data. Read more about our research themes and
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desired. Knowledge on statistical methods and their application is an extra merit. Good knowledge in GIS and R is a merit. Proven excellence in written and spoken English is essential. The fieldwork will
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will use machine learning methods to develop affinity ligands. These methods have been transformative for protein design, allowing generation of novel proteins which can suit a precise need. In this 4
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novel machine learning method development. However, you will be part of a larger cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities
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ecology, and/or restoration ecology. Experience in design, execution and analysis of acoustic data is desired. Knowledge on statistical methods and their application is an extra merit. Good knowledge in GIS
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energy, energy storage, electronics, medicine, sustainable manufacturing, etc. The main focus for the advertised position is novel machine learning method development. However, you will be part of a larger
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information about the program can be found at Doctoral studies at the Faculty of Medicine . Background and description of tasks The PhD student will use state-of-the-art methods such as cryo-electron tomography