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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
applicant will contribute to the AIGLE project by: · Developing innovative scientific Deep Learning/Machine Learning algorithms for flash flood forecasting. · Contributing to the collection
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 23 hours ago
more advanced concepts such as tools for supervised/ unsupervised learning that will be helpful for deep learning focused courses. Estimated course enrolment: 35 Estimated TA support: 1 Class schedule
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Engineering in the 2025 QS World University Rankings by Subjects. The EEE Rapid-Rich Object SEarch (ROSE) Lab focuses on research in: (i) visual search & retrieval, (ii) video analytics & deep learning, and
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(particularly Deep Learning), will also make it possible to leverage the collected data to enrich knowledge of ovine behavior. The candidate will join a dynamic research group within the Image/Vision team
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for Machine Learning (AIML) is the largest university‑based machine learning research group in Australia and the country’s first institute dedicated to advancing machine learning, computer vision, deep learning
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have strong programming skills in Python; You have knowledge of medical image processing, and machine learning and deep learning techniques; Written and spoken proficiency in (scientific) English is
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: Required: • MSc (or equivalent) in: Computer Science, Cybersecurity, Machine Learning, or related field • Strong background in: machine learning / deep learning, mathematics (probability, linear algebra
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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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. The successful candidate will pursue an active research agenda and contribute to the Climate Policy Lab?s ongoing projects, as well as contribute deep expertise in either China, Latin America, or system dynamics
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, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap camera footage for wildlife monitoring and conservation efforts. Job Responsibilities