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reduced teaching responsibilities. We are a federal competence center for AI education and research. Our research pushes the boundaries in numerous aspects of intelligence, including algorithms and models
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. This includes, but is not limited to: machine learning algorithms, formal proof assistants, and large language models. Areas of interest for possible collaborations include but are not limited to: topological
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the deployment, operation, and maintenance of seismic stations and associated equipment for field data acquisition. Develop, implement, and optimize artificial intelligence (AI) algorithms for the automatic
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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
interested in recruiting faculty members who use and develop artificial intelligence methods and mechanistic mathematical models to address fundamental questions in biology. Examples of research topics include
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algorithms. Implementation Expertise: Outstanding scientific programming skills (Python, PyTorch/JAX) with a proven track record of developing, debugging, and scaling complex RL pipelines or custom simulation
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algorithms, and some knowledge of data science and machine learning (through coursework, self-learning, or personal projects). The selected student will work with Ph.D. and master's students to help develop
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to support reliable DAS interpretation and urban infrastructure monitoring. Key Responsibilities: Develop automated, uncertainty-aware algorithms to infer and map fiber-optic cable routes from DAS-derived
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-impact projects across our core focus areas. We are looking for curious minds who are excited to push the boundaries of responsible AI. Learn more about the lab's work at: https
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with algorithm software development and user interface design. Key Responsibilities: Collect relevant traffic data from several resources, working with industrial collaborators. Carry out necessary data analytics
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results Job Description Primary Duties & Responsibilities: Designs, develops, and implements: Algorithms and computer software for omics-based data sets [high-throughput, massively parallel genomic