105 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UCL" Postdoctoral positions in Sweden
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at understanding the mechanisms underlying context-dependent human social learning of affective responses and social values. In this role, you will work at the forefront of research, developing new
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fundamental research in robotics autonomy with a strong European and National participation in multiple R&D&I projects. RAI has participated in the DARPA SUB-T challenge with the CoSTAR Team lead by NASA/JPL
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multiple R&D&I projects. RAI has participated in the DARPA SUB-T challenge with the CoSTAR Team lead by NASA/JPL (https://costar.jpl.nasa.gov/ ). Subject description Robotics and artificial intelligence aim
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search and rescue, multi sensorial fusion and multirobot coordination, including multirobot perception, decentralization and mission execution. The RAI team has a strong European participation in multiple
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, decentralization and mission execution. The RAI team has a strong European participation in multiple R&D&I projects, while RAI was also participating in the DARPA SUB-T challenge with the CoSTAR Team lead by NASA
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around 15 are PhD students. The work environment is open and welcoming, striving to provide each employee with the opportunity to develop personally and professionally. The field of solid mechanics relates
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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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deals with international trade in forest-based products, focusing on the trade between Sweden and Norway and other regions. The post-doctor will develop an analytical framework able to account for bi
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nationalities, backgrounds and fields. As a postdoctoral researcher, you receive benefits in career development, networking, administrative and technical support functions, along with good employment conditions
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mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering