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Position as Computational Analyst / Bioinformatician in RNA Therapeutics and Cardiometabolic Disease
. Proficiency in at least two of the following programming languages: Python, R. Experience in Machine Learning and Computational RNA Biology are desirable. Hands-on experience or understanding (the limitations
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to conferences. Research and teaching efforts at a section and departmental level as appropriate and relevant (e.g., teach and supervise PhD and MSc student projects). Qualification You should have a background
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Position as Computational Analyst / Bioinformatician in RNA Therapeutics and Cardiometabolic Disease
datasets. Proficiency in at least two of the following programming languages: Python, R. Experience in Machine Learning and Computational RNA Biology are desirable. Hands-on experience or understanding
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to conferences. Research and teaching efforts at a section and departmental level as appropriate and relevant (e.g., teach and supervise PhD and MSc student projects). Qualification: Background in concrete
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, or a related field) A relevant MSc degree (e.g., Computer Science, Software Engineering, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field) Strong skills in machine
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mechanics, vibrations, and their active control, as well as machine elements and design optimization. The section has a scientific staff of about 25 people and 20 PhD students. The research rests
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have: A relevant PhD degree (e.g., NLP, AI, ML, Security, Cryptography, or a related field) A relevant MSc degree (e.g., Computer Science, Software Engineering, Machine Learning, Artificial Intelligence
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Professor (tenure-track) and/or Associate Professor levels with a focus on Data Science and Machine Learning. The expected starting date is summer 2026, with room for flexibility. Depending on the profile
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well as experience in automated fabrication and mechanical characterization. A solid background in modelling and system identification is essential, with particular emphasis on data-driven and machine-learning–based
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++, Phyton, and machine learning is necessary as well as excellent communication skills in English. Applicants with experience in digital energy, and if possible, co-simulation frameworks such as FMI/FMU, will