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developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1
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at the interface between computational design and in vitro experiments, the team has developed multiple in silico and in vitro methods to design novel antibodies and nanobodies as therapeutic agents and research
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Princeton Laboratory for Artificial Intelligence (the “AI Lab”) invites applications for a full-time Research Software Engineer (RSE). As an RSE joining the AI Lab, you will contribute
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water, etc.) by fusing sensor data (e.g. sonar, INS, USBL). Collaborative control strategies: Developing coordinated control algorithms that allow the USV and UUV to perform joint missions without
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detailed local inspection. Digital twin simulations: Developing simulation environments replicating sensor characteristics and anomaly conditions to test perception algorithms under controlled, repeatable
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-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging techniques influence
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institutions, and leading industry partners. The successful candidate will contribute to the delivery of high-impact research projects involving AI algorithm evaluation and image data analysis. You will play a
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demonstrate the ability to use this background to: Develop innovative decision-making strategies that seamlessly integrate operational research techniques and machine learning algorithms. Engineer solution
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facility at the University of Queensland. We’re seeking a Research Scientist/Engineer to help develop next-generation quantum technologies. In this role, you’ll work within our Quantum Systems Team to: Drive
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aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will support the development