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(Wissenschaftszeitvertragsgesetz - WissZeitVG). A shorter contract term is possible by arrangement. The position aims at obtaining further academic qualification. Professional assignment: Chair of Machine Learning for Spatial
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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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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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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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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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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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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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
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. Specifically, the PhD candidate is expected to contribute corpora preparation (collection and organizing the annotation), use machine learning approaches for irony detection, and testing for experimental and