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Field
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familiar with data analysis using programming languages like R, and/or Python. You have excellent communication skills and a willingness to collaborate across disciplines. You fit to us: if you have strong
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expertise in object-oriented programming in Python, data modeling, and scientific workflows experience in collaborative Linux-based development using Git knowledge of Python-based type systems and schemas
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data analysis using software Experience in R and python is a plus but not mandatory Good presentation and writing skills Proactive, independent, and solution-oriented way of working Fluent English
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Knowledge in the field of Machine Learning, including training, inference, and optimisation of transformer architectures Knowledge in the field of ML security is desirable. Good Python skills, especially with
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part of the Forschungsverbund Berlin (https://www.fv-berlin.de/) and the Leibniz Association (https://www.leibniz-gemeinschaft.de ). You can find more details on the institute webpage: https://www.ikz
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sampling strategies in Python and C++ Apply your framework to analyse real biological datasets to demonstrate robustness, interpretability, and practical impact Contribute to open-source software tools
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Engineering, or a related field Strong programming skills in Python and SQL; experience with C/C++ Experience in data modelling and dimensional modelling Experience with CI/CD workflows for data and software
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data analysis using software Experience in R and python is a plus but not mandatory Good presentation and writing skills Proactive, independent, and solution-oriented way of working Fluent English
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of machine learning or quantum computing Programming skills in Python and/or C/C++ Experience with scientific software tools and numerical libraries Familiarity with Linux-based computing environments Ability
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present. Evaluation of the trained models on suitable datasets. What you contribute Good knowledge in the field of machine learning and training neural networks. Good Python skills, preferably some