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for one to two PhD students in analytical chemistry to develop analytical methods for single cell analysis and mass spectrometry imaging using direct infusion mass spectrometry. The PhD candidate will work
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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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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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information about us, please visit: the Department of Biochemistry and Biophysics . About the DDLS PhD student program Data-driven life science (DDLS) uses data, computational methods and artificial
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spectrum, in topics in virology and immunology, and currently specializes in computational biology focusing on developing methods and applications of deep learning for protein sequence and structure, as
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experience working with deep learning methods for biomedical applications. Academic and Project Excellence: Evidence of high-quality research work, as demonstrated by academic grades, the merit of prior degree
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life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health