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Field
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the opportunities and challenges presented by artificial intelligence. Bowdoin College offers opportunities for professional development, a fully-funded, year-long pre-tenure sabbatical leave (after three years
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to the development of data algorithms and specialized computer software for identifying and classifying components of biological systems (such as DNA and protein sequences). Support the creation and maintenance
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that require a high degree of expertise, creative insight and technical skill, resulting in advances beyond the current limitations of MEG technology; and will develop novel solutions that address long standing
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research Engineer in Autonomous Drone Navigation for Maritime Environments to develop safe and
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EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites | Darmstadt, Hessen | Germany | 2 months ago
. Responsibilities include the development and maintenance of scientific software tools, primarily in Python, for performance monitoring, anomaly investigation, and algorithm evolution. The role requires the ability
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, the Student Assistant develops social media campaigns, captures photo and video content, designs marketing materials, and represents the department at campus outreach and recruitment events. The Student
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of the internship: Machine Learning for recognition of planetary materials from multispectral datasets You are sought to contribute to the ongoing development of Machine Learning algorithms for recognition
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this project, you will design a system and develop a first feasibility prototype for such a device, based on photonic sensing technology and advanced data analysis techniques. Your responsibilities include
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, and Rust for speed-optimized algorithm implementations. Projects will entail development of command line tools, APIs, and cloud-based web services (both public and private cloud). Establish and maintain
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analysis using simulation-based inference (SBI) with domain adaptation techniques. The work centers on developing robust, transferable inference pipelines that bridge the gap between synthetic simulations