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the PORTUGAL2030 Programme, under the following conditions: Work Plan and Objectives to Reach: The work to be carried out aims at the research and development of Computer Vision and Machine/Deep Learning algorithms
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Engineering & Applied Physics Program. This position covers AI hardware with a focus on quantum computing, quantum communication, quantum sensing, and quantum simulation. The successful candidate will develop
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essential for learning complex distributions over structured data such as text, graphs, and biological sequences. Developing and understanding models for dis- crete spaces is therefore a key challenge in
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one day a week on campus. Job description The computational biologist will be expected to: Lead the development of acoustic detection and classification algorithms for marine mammals. Evaluate algorithm
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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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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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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, 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