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for probabilistic unsupervised learning for structured biological data. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/307053/3-years-phd-position-in-probabilistic-machine
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welcomed. The project sits at the intersection of statistical genetics, systems biology, and machine learning, with strong emphasis on methodological development. Tasks of the PhD Student - Develop and
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biological domains is a must PhD in computational biology, computer engineering, computer science, (bio)statistics, artificial intelligence, physics, or related. Desire to push the frontier
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and predict how the immune system responds to interventions. This tight integration of advanced machine learning and experimental immunology allows us to tackle fundamental biological questions with
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, computational biology, statistics or a closely related field. You have strong programming skills, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision
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).The PhD candidate is expecting to assisting in teaching and help in laboratory on the related topic. Applicants should fulfil the following requirements: A Master's degree in computer engineering, computer
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application! We are now looking for 1–2 PhD students for the Division of Computer Vision and Learning Systems at the Department of Electrical Engineering (ISY). Your work assignments Within the research unit
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on large-scale numerical simulations, instrumented experiments, and onboard robotic data could learn generic representations of local interactions between mobile robots and their environment, enabling
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learning and data science professional who wants to make a real-world impact? Do you have a specialisation in machine learning and affinity with project management? Do you want to apply advanced AI solutions
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | about 2 hours ago
. or Diploma in bioinformatics or a comparable qualification Extensive programming experience Practical experience in machine learning and the application of large language models Knowledge of OMICS and image