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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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research with the aim of understanding molecular processes in prokaryotic cells and/or interactions between cells. Subject Prokaryotic microbiology with focus on molecular processes Subject description
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the genetic material, and how it interacts with various kinds of micro-organisms. Using this knowledge, we try to elucidate the causes of diseases, and find new ways to diagnose and treat them. The Institute is
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) for life science research projects are important to understand the computational methods. Extensive (3+ years) experience of applying and/or developing advanced digital image analysis methods in the field
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KTH Royal Institute of Technology, School of Engineering Sciences Job description The AICell Lab (https://aicell.io ) in the department of Applied Physics at KTH and Science for Life Laboratory is a
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, imaging data, and cell and molecular biology. These services are developed based on the needs of SciLifeLab users and as part of the Data Centre’s mission as a provider of digital infrastructure. The work
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qualifications Publications at top machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR, AISTATS etc.) are highly meriting. Expertise in Bayesian methods, generative models, multimodal models
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the physical mechanisms of infection. We are based at KTH and SciLifeLab in Stockholm (https://hannebellelab.org/ ). We are seeking a PhD student to study the biophysics of schistosome skin infection
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analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https