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complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
abiotic resources. We integrate remotely sensed information with in-situ data, process-based models, and leverage satellite communication, IoT and machine learning technologies in order to provide evidence
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science, and educators to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater understanding to the world. For more
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machine learning, computer vision, and medical image analysis, with publications in top-tier AI and medical image analysis conferences and journals, including CVPR, ICCV, ECCV, NeurIPS, MICCAI, TPAMI, TIP
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Supervisor: Dr. Kamila Maria Jozwik, Jozwik lab PhD fees status: Home fees only (https://www.postgraduate.study.cam.ac.uk/finance/fees/what-my-fee-status ), 4 years Start date: October 2026 The
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for a full-time lecturer position. The appointment will be effective August 2026. Successful candidates must be able to teach in-person human anatomy and physiology lectures and labs. Candidates should
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inference, longitudinal methods, survival analysis, regression modeling, machine learning, or prediction modeling are required, as well as experience with statistical software such as R, SAS, or STATA. Prior
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Computer Science, Electrical/Electronics Engineering, Data Science, Cyber-Physical Systems, or a closely related discipline. Machine Learning & Data Processing: You have solid experience developing and applying
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 25 days ago
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Position in Machine Learning for Single-Cell Genomics (f