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Specific Responsibilities/activities: Maintaining long-term observational capabilities Participating in intensive field campaigns Designing novel tailor-made algorithms and inversion methods Combining
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. The project will be carried out in a stimulating biology- and molecular medicine-oriented research environment shared with multiple principal investigators capable of attracting several important international
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and dynamics, which we also plan to investigate using AI-based pattern recognition algorithms. In this project, the PhD student will: Run the MIT General Circulation Model (MITgcm) together
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(rhizotron facility) and field trials. In addition to field applications, novel inversion algorithms for ground-penetrating radar (GPR) and electromagnetic (EM) will be developed. These algorithms will enable
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Together, these research directions seek to reimagine how buildings and cities operate—optimizing energy use, enhancing human well-being, and reducing carbon emissions at scale. We are seeking multiple
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understanding of statistics and familiarity across multiple biological fields of study. Exceptional organizational skills with strong attention to detail in data management, record keeping, and laboratory
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research associate position in AI for science. The Learning Systems Group seeks a postdoctoral researcher specializing in federated learning and privacy-preservation algorithms. The successful candidate will
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figures of lab members. Candidate will train on the lab’s fundamental algorithms and run them in a collaborative manner with other team members to generate paper figures and make discoveries. Collaborative
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optimize algorithms for analyzing behavior data. Build or implement existing scripts to temporally align data across multiple modalities. Coordinate efforts with DNB researchers and established vendors (Med
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experience with, statistical methods and machine learning algorithms applied to climate science research challenges. They must be highly organised and motivated and should demonstrate aptitude for programme