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of potentially novel modes of protein binding is possible in collaboration with other members of the lab. Desired (but not absolutely required) skills: programming in python, machine learning, and experience in
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performing data analysis of B cell receptor repertoire data using programming languages (mostly R) Successful candidates can think independently, are eager to acquire necessary new skills, and are excellent
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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qualifications. You will teach students in accordance with the teaching regulations of the state of Hesse in the subjects “Animal Physiology” and “Neurobiology”. You will carry out research projects with a focus
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qualifications. You will teach students in accordance with the teaching regulations of the state of Hesse in the subjects “Animal Physiology” and “Neurobiology”. You will carry out research projects with a focus
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to doctoral researchers aiming for successful careers in science. Our comprehensive curriculum allows our students to tailor their learning to their interests, requiring them to earn 25 ECTS through various
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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-class graduates with expertise in the CRC-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, openness for internationalization and diversity, very good verbal and
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms