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. Are you interested in applying your machine learning and deep-learning expertise to develop cutting-edge ecological and environmental research? The Senckenberg Gesellschaft für Naturforschung invites you to
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how such systems operate in practice, exploring their social and policy impact, or developing technical or regulatory mechanisms that support transparency, oversight, and accountability. The position
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the opportunities and challenges of the datafication and algorithmization of society, culture, and human knowledge in the age of AI. You will play an active role in developing an innovative departmental profile
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holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms (AI) to analyze large imaging and molecular
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to co-design algorithms and circuits to develop efficient neuromorphic hardware, tailored to target tasks. In detail, you will: develop circuit-plausible training/inference algorithms and analyze in
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, but also in traffic monitoring or in the media context, for example when it comes to automatic metadata extraction and audio manipulation detection. Another focus is the development of algorithms
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algorithms into an existing framework, with a focus on efficiency, as well as creation and execution of relevant simulation pipelines: from real data to mathematical and clinically actionable results
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and quantum computing. Develop innovative AI workflows, revolutionize the research process and find solutions to everyday problems. Become part of a dynamic, interdisciplinary team where pioneering
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software frameworks Development of new signal processing algorithms (PHY/MAC) in conjunction with software-defined radio hardware Development and validation of AI/ML methods for mobile communications systems
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Everyone is talking about artificial intelligence. But who is developing the necessary chips? We are, for example! Would you like to help drive the development of a new highly efficient AI hardware