12 computational-physics "https:" "https:" "https:" "https:" "Chalmers" Fellowship positions at Carnegie Mellon University in United States
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Carnegie Mellon University, Institute for Computer-Aided Reasoning in Mathematics Position ID: 3637-PF [#27988] Position Title: Position Type: Postdoctoral Position Location: Pittsburgh
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recognize multimodal human behavior in real world settings (e.g., Affective Computing, AI for Healthcare: pain measurement, monitoring mental health disorders). The successful candidate will have primary
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project. This position will require an in depth knowledge of a specialized field, process, or discipline and may involve organizing and implementing complex research plans, the development of methods
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bioconjugation and polymer processing. Core Responsibilities: Develop strategies to tune the physical and chemical properties of proteins through chemical modification Develop methods to compatibilized proteins
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an in depth knowledge of a specialized field, process, or discipline and may involve organizing and implementing complex research plans, the development of methods of research, testing and data collection
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manipulation with physics-based simulation in the loop. Mentoring graduate and undergraduate students. Other duties as assigned. Adaptability, excellence, and passion are vital qualities within Carnegie Mellon
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of computer graphics, human-computer interaction, computer vision, and machine learning. Conducting comprehensive literature reviews in related areas, including deep generative models, image and video synthesis
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for the Pitkow Lab. Core Responsibilities Include: Develop computational methods for inference and control that improve the reliable and efficient operation of autonomous agents in complex, uncertain environments
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computational biologists. Publishing research findings in peer-reviewed journals and present at scientific conferences. Mentoring and supervise graduate and undergraduate students in related projects
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technical/computational backgrounds (ML, NLP, AI safety, working with LLMs) as well as computational social scientists. The ideal candidate bridges these worlds or is eager to learn across them