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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting
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aims to build predictive and physical binding models of protein – DNA interactions using high-throughput and quantitative biochemical binding data across hundreds of thousands of sequence variants
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and motivated PhD student to join an interdisciplinary project that combines computational biology, spatial transcriptomics, and tumor modeling to understand how the aggressive brain tumor glioblastoma
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vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
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The doctoral student project and the duties of the doctoral student This Data Driven Life Sciences (DDLS) PhD project focuses on probabilistic models of protein structure, which can be used primarily
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networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and
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methods in applied mathematics and computational modeling, this specific project aims to uncover new insights into how blood cells form in both healthy and disease states. A key objective is to model
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) biological knowledge about GRNs from bioinformatics and system biology, (b) graph theory and topological data analysis for network modeling from mathematics, and (c) robust machine learning (ML) and GenAI from
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study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required. The research group Our lab is advancing precision medicine through deep learning models
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research and methodological development to design and implement novel computational models and solutions. A solid theoretical background and hands-on experience in digital image processing and deep learning