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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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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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(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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engineering or similar. Knowledge and experience with deep learning models applied in computer vision. Remarkable academic trajectory, validated by a strong record of publications in relevant international
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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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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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: https://www.jobbnorge.no/en/available-jobs/job/294558/phd-research-fellow-in-deep-learning-for-imaging-of-marine-ecosystems Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294558/phd
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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
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/359354/2-phd-positions-on-learning-cau… Requirements Additional Information Website for additional job details https://www.academictransfer.com/359354/ Work Location(s) Number of offers available2Company
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Description We are seeking a motivated new PhD candidate who wants to join an exciting collaborative research program within the VIB-Center for Inflammation Research between the Guilliams, Saelens