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, Stockholm Solna. Due to the highly interdisciplinary nature of the project and the position (applied mathematics), the successful candidate will also be an integral part of Johan Karlsson’s group at KTH
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Admission to Doctoral (PhD) Studies in the subject Engineering Sciences with specialization in Biomedical Engineering at the Division of Biomedical Engineering, Department of Materials Science 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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Are you passionate about applying computational approaches to solve problems in biomedicine? We are now looking for an Industrial PhD student in Data-Driven Life Sciences to work on a cutting-edge
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Are you passionate about applying computational approaches to solve problems within chemistry and biology? We are now looking for an Industrial PhD student in Data-Driven Life Sciences to work on a
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KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science Project description Third-cycle subject: Computer Science This project involves generative modeling
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chemistry, materials chemistry, inorganic and structural chemistry and organic chemistry. The research projects are many from theory to experiment, from basic research to more applied projects often focusing
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will combine state-of-the-art computer vision, modeling and archived specimens to determine biotic and abiotic factors driving spatial variation in molt phenology. It will use museum genomics to recover
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method for understanding complex genomic alterations. While sequencing technologies have made a leap forward, work is still needed on the computational side to fully use the technology. This is an
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collaboration with the co-supervisors and their labs, the project will also involve the use of these methods (and methods developed by others) for applications in infection biology, chiefly for designing