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Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
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the main deliverables to the consortium before 31 December 2028. In the remaining time of this position, the PhD candidate can write and finalize the thesis. Where to apply Website https
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. In addition, you must have: a solid foundation in energy technology and a strong understanding of artificial intelligence (AI), machine learning (ML), and data-driven modeling documented experience
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/or spatial genomics, computational biology, machine learning, bioinformatics, and systems neuroscience. Prior experience with deep learning applied to biological data is a plus. Practical experience
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education. Connections working at Princeton University More Jobs from This Employer https://main.hercjobs.org/jobs/21923150/2025-postdoctoral-research-associate-ai-machine-learning-for-analytical-and-forensic
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opportunity to contribute to leading-edge research at the intersection of applied machine learning and clinical dental practice. As a member of our team, you will help translate contemporary data science
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; GIS; environmental data analysis; machine learning; numerical modelling; tracer experiments; dispersion and mixing. DESCRIPTION (topic, expectations, comments): We are seeking a researcher holding a PhD
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Machine Learning A PhD position is available at the Computer Vision Center (CVC) under the supervision of Fernando Vilariño and Paula García . The successful candidate will be enrolled in
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theory and methods by taking several PhD-level courses (about 36 European credits) in information systems, operations management, econometrics, machine learning, extensive data analytics and qualitative
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probabilistic frameworks. Experience with machine learning or AI methods for localization or perception (e.g. learning-based SLAM, data-driven sensor fusion) is a plus. Underwater or field robotics experience