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learning of autonomous vehicle systems. The AVS Lab's research is motivated by the goal of developing the next generation of intelligent autonomous vehicle systems. We are seeking for highly motivated and
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learning of autonomous vehicle systems. The AVS Lab's research is motivated by the goal of developing the next generation of intelligent autonomous vehicle systems. We are seeking highly motivated and
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challenging PhD programs, which will supplement your research training with outstanding opportunities for career development, continued education and life-long learning. Situated on the foothills of the Alps
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an amount of 1,575 EUR per month. For expenses directly related to the doctoral project (e.g. learning materials, travel), an additional subsidy may be granted on submission of receipts. Application Papers
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to suitability, performance, and capability is based on the German TV-L full-time scheme and is limited to 3,5 years. Contracting is in accordance with the German „Wissenschaftszeitvertragsgesetz“. Severely
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group, a multinational insurance company. Tasks Your duties will include: Literature research Designing, implementing, and evaluating novel machine learning approaches to detect building attributes from
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to suitability, performance and capability based on the German TV-L full-time scheme and is limited to 3 years. Contracting is in accordance with the German „Wissenschaftszeitvertragsgesetz“. Severely disabled
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for this position, the candidate should possess in-depth skills in programming and hands-on training and evaluating machine-learning models. Expertise in in the field of Building Information Modelling and geometric
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of specialization include: Web Application Engineering Model-based Systems Engineering AI for Software Engineering Software Engineering for ML Big Data Architectures Cloud Architectures Contribution to Software
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scientists from different fields, working on current research fields. The employment contract, including remuneration, is based on the collective agreement for the public service of the federal states TV-L EG