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Uppsala University, Department of Information Technology Are you interested in probability theory, statistics, and mathematical modelling? Would you like to develop new methods for uncertainty
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. At the Division of Systems and Control , we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and
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, represented as a set of raw sequences, graphs, or sequence alignments. In this project, we will conduct a comparative study of noncoding genomic regions. You should have expertise in algorithm design and high
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computer science, image analysis and machine learning, engineering physics, data science, applied mathematics, molecular biotechnology engineering, or another related field; or Have completed at least 240
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Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Mathematics and Computer Science, Department of Information Technology Are you interested in working with probabilistic
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completed courses. Earlier specialization in machine learning, control theory or mathematics is highly desirable. After the qualification requirements, great emphasis will be placed on personal skills. Target
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Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Mathematics and Computer Science, Department of Information Technology Are you interested in working with machine
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Job description Quantitative analysis of lipid nanoparticles (LNPs) using Cryo EM is challenging due to heterogenous samples, lack of training data and sample variability. In this project we aim to develop AI/ML...
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. Required qualifications: PhD in a field such as physics, systems biology, applied mathematics, machine learning, or related fields. Strong programming skills (e.g. Python) and experience with modern ML
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predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming, mathematics, physics. You will