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hypotheses. This is a fantastic opportunity to contribute to world-class science in a leading biotechnology company. Who you are: Candidates must have a PhD in Computational Biology or Computational Science
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supervisors and fellow researchers, you will contribute to the development of solvers for combinatorial optimization problems and apply them to real-world data from industrial partners. As part of your PhD, you
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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address: Dr Fahad Panolan: f.panolan@leeds.ac.uk Project summary The Algorithms group at the University of Leeds (UK) is offering a fully funded 3.5-year PhD studentship on Parameterized Complexity and
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independently, has a passion for AI and its applications, and is willing to learn new technologies. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills
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include: · building hierarchical causal graphs to account for the multi-scale structure of the experimental system, · detecting latent variables that may affect causal inference
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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, computational statistics, statistical machine learning, statistical data science, modeling and inference for networks and graphs, optimal decision-making, stochastic spatio-temporal modeling, statistical AI, and
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institutes in Berlin which are funded by the federal and state governments. The research institutes belong to the Leibniz Association. WIAS invites applications as PhD Student Position (f/m/d) (Ref. 25/11) in
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structural and algorithmic graph theory. The purpose of the role is to contribute to the project “Algorithmic meta-classifications for graph containment”, working with Professor Matthew Johnson, Dr Barnaby