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developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1
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in high-performance computing, materials chemistry, theoretical chemistry, molecular dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive
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technology. What you will do As part of an internship, we offer you the opportunity to deepen your interest and knowledge in the field of machining. You will learn how to use CNC machine tools and manufacture
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established that reliably identifies the connected components in the diagrams. You will learn about novel AI models and exchange ideas with experts from the building sector. The "Image Processing and Machine
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, check your computer’s network connection. If your computer or network is protected by a firewall or proxy, make sure that Firefox is permitted to access the web. You can continue with your default DNS
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or CNC machines You have already worked with Python or other data analysis software, or are motivated to acquire the relevant skills What you can expect 👥 Team spirit: Creative and interdisciplinary
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of interest include, but are not limited to: AI methods that meet the complexity of living systems, high-dimensional machine learning for biology, statistical machine learning, AI‑driven laboratory automation
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for industry. To this end, the latest findings from the fields of artificial intelligence, machine learning and cloud-based methods are combined with proven expert knowledge to answer current questions in robot
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Curriculum and other under and post graduate degree programmes that involve the Faculty of Medicine. Further, they will be expected to teach in areas outside their specialisation. The successful candidate will
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novel machine learning-guided approaches. The position is located at TUM Campus Heilbronn. Your qualifications Strong background in computer science, AI, or related areas or similar fields. Solid