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Graduate School training programs. Qualifications The applicants should possess: an excellent or very-good university degree in agricultural or resource economics, applied economics, agricultural sciences
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master’s degree in mathematics, theoretical computer science, machine learning, or a closely related field. Strong background in discrete optimization, algorithms, or reinforcement learning. Good programming
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informatics, or a related field - Strong programming skills in Python and experience with deep learning frameworks (PyTorch preferred) - Experience or strong interest in large language models, multimodal
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, ecology, mathematics, or a related field Strong programming skills, preferably in Python (experience with scientific computing, ML frameworks, high performance computing and geospatial data are highly
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command of written and spoken English • Experience with qualitative research methods is an asset • Good knowledge of machine learning /data mining in science • Good programming skills in at least one
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integration into TUM’s School of Life Sciences or School of Management and participation in the related Graduate School training programs. Qualifications The applicants should possess: - an excellent or very
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or School of Management and participation in the related Graduate School training programs. Qualifications The applicants should possess: - an excellent or very-good university degree in economics
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. The application should contain a letter of motivation, a CV including publication list, (degree) certificates, and at least two possible references. Please send your application as a single pdf-document by email to
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their thesis work in the field of robotics; Strong programming skills in C++ and/or Python, as well as experience in implementing robot learning algorithms; A strong background in control theory, machine
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or School of Management and participation in the related Graduate School training programs. Qualifications The applicants should possess: an excellent or very-good university degree in economics strong