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, and benchmarking of novel algorithms on synthetic and real-world datasets Development and maintenance of open-source research software and reproducible workflows Collaboration with CRC partners across
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robotics Goal-driven agentic AI Autonomous medical imaging Design of AI-enhanced medical devices Machine learning models and algorithms for medical signal processing Embedded AI Privacy-aware AI Foundations
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predict food-effector systems. Key Responsibilities • Develop graph-based (multi-)omics analysis algorithms • Benchmark graph-theoretic against graph-ML approaches • Analysis of food-related (multi-)omics
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Your Job: Join our team as a dedicated scientist and contribute to our exciting research projects. Our work focuses on models and algorithms for supervised and unsupervised learning. We devise deep
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(rhizotron facility) and field trials. In addition to field applications, novel inversion algorithms for ground-penetrating radar (GPR) and electromagnetic (EM) will be developed. These algorithms will enable
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support and training in classical and quantum modeling, quantum algorithms and computation, and battery materials and technology Further development of your personal and interdisciplinary strengths through
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, internationally oriented center for cutting edge research on neurodegenerative diseases. We are seeking a highly motivated and skilled Postdoctoral Researcher to develop new algorithms for multi-omics data
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classical and quantum modeling, quantum algorithms and computation, and battery materials and technology Further development of your personal and interdisciplinary strengths through a range of training
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optimizing reaction conditions compared to human decision making and design of experiments techniques. We will develop a Bayesian optimization algorithm for the optimization of reaction yields
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) and the University of California Irvine (UCI). The Research School "Foundations of AI" focuses on advancing AI methods, including energy-efficient and privacy-aware algorithms, fair and explainable