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Field
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) Experience with programming languages (ideally Python) Fluent in written and spoken English Very independent and self-motivated way of working but also excellent teamwork skills High motivation to take on
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important - Prior experience with density functional theory or machine learning is desirable - Proficiency in the Python programming language is important, as well as Fortran - Strong written and oral
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in transcriptomics, epigenomics, and/or genomics Strong analytical skills, as well as broad experience with scripting languages (e.g., Python, R, Bash); knowledge of common bioinformatics software and
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via Ethernet as well as data processing and data synchronization within linked systems. Know-how in EMC-compliant assembly of electrical systems would be a plus. Programming skills with Python and C/C
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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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support, utilizing pharmacokinetics database PK-DB and individualized patient data (more information: https://livermetabolism.com/atlas ) Requirements: - completed scientific university degree in (bio
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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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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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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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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