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processing, quality control, integration, and analysis of single‑cell and multimodal omics datasets (e.g. scRNA‑seq, scATAC‑seq). Train, evaluate, and benchmark deep learning models operating on single‑cell
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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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processing, quality control, integration, and analysis of single‑cell and multimodal omics datasets (e.g. scRNA‑seq, scATAC‑seq). Train, evaluate, and benchmark deep learning models operating on single‑cell
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Europe Marie Skłodowska-Curie Actions Doctoral Network (MSCA DN) COMBINE. The successful candidate will undertake research on: Deep learning for solidification in multiphase flows with radiative heat
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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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(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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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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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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computing subjects, including artificial intelligence. In addition, you will be able to demonstrate specialist expertise in one or more of the following areas: - Machine learning and deep learning