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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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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | 1 day 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
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with a strong background in mathematics, computer science, or machine learning. The work has a strong focus on developing new objectives or new architectures for medical deep learning and on new ways
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influencing factors and improve the accuracy, robustness and energy efficiency of intelligent sensing systems. Apply AI as an engineering tool: Use signal processing, statistical methods and machine learning
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and (2) develop learning rules that are both technology-feasible and well-suited for machine-learning workloads. The project will consist among others of the following tasks: Investigate and design
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-trivial software. Solid understanding of algorithms, numerical methods, scientific computing, or machine learning. Ability and motivation to write clean, maintainable and well-tested code. Strong interest
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | 3 months ago
fields Experience with image analysis, or computer vision Good knowledge of basic machine learning techniques, such as variational autoencoder Good presentation and writing skills Proactive, independent
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computer simulations Working in close collaboration with theoretical physicists to test models and develop new insights Your Profile Bachelor's degree in physics Master’s degree/diploma in condensed matter
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or complementing traditional physics-based approaches by data-driven ones, using Machine-Learning (ML). Such approaches allow enormous gains of time, in a way that can be related to the astonishing efficiency
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are interested in combining disciplinary knowledge with the skills of a data scientist and working at the interface of bioinformatics, medical informatics, databases, data mining, machine learning, applied