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learning methods to understand and investigate the functional behavior of gender-specific cancers. The work will include: Development of ML/DL methods for multi-omics data analysis. Design and implementation
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epidemiology and biology of infection, which is a fully funded, four-year PhD student position. Data-driven life science Research School Data-driven life science (DDLS) uses data, computational methods, and
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. The project focuses on developing novel representation learning and generative modeling methods to construct a unified cellular morphology state space across heterogeneous datasets. By leveraging shared
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Project description Third-cycle subject: Biotechnology The project aims to develop methods in three-dimensional spatial
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methods for analysis of cellular and molecular biology data. The host institution, The Department of Gene Technology , is the most prominent research environment at KTH, according to bibliometrics
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contribute new and better ways to analyse and interpret large-scale data. In your position, you will develop computational methods for cryo-EM reconstruction, heterogeneity analysis, and modeling of structural
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protein analysis methods Preferred qualifications Experience from biotech/pharmaceutical industry or relevant academic research environment Experience with structural biology, especially cryo-EM Experience
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internationally outstanding research in the life sciences. Project description We seek two highly motivated postdoctoral researchers to develop new mathematical and computational methods for modeling developmental
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of very different backgrounds Ability to collaborate and work in a service-oriented organization. Willingness to learn new methods and the ability to develop new skills. Ability to manage projects
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dynamics of complex molecular systems, and relationships between the presence of biomolecules and synthetic chemical compounds with various disease states. There is also strong research in method and