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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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qualifications Documented experience with data analysis and programming (e.g., Matlab, Python or R). Experience of risk assessment and/or decision analysis Experience of probabilistic methods such as Monte Carlo
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sequencing, and with computer scientists at KTH in Stockholm, focused on developing scalable probabilistic machine learning techniques for online phylogenomic analysis and placement of DNA barcodes. You will
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the development team of TreePPL (www.treeppl.org ), a universal probabilistic programming language and new software for phylogenetics. The successful candidate will be responsible for the user-interface aspects
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attributes are shifting in the presence of probabilistic outputs, non-determinism, and continuous data dependencies, and how these factors impact maintainability, testability, and reusability. The PhD project
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team of TreePPL (www.treeppl.org ), a universal probabilistic programming language and new software for phylogenetics. The successful candidate will be responsible for the user-interface aspects
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will be working within the development team of TreePPL (www.treeppl.org ), a universal probabilistic programming language and new software for phylogenetics. The successful candidate will be responsible
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activity recognition, anomaly identification/detection, and prediction/forecasting using real-world datasets. Duties You will take Ph.D. courses while performing thesis work in the form of, for example
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. The work is performed in connection to two ongoing research projects “Probabilistic multiscale modelling of the macroscopic crack growth behavior in heterogeneous materials” and “Optimized Digitalization