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Field
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clinical approaches, including: Histopathology and digital pathology (whole-slide imaging, WSI) Quantitative analysis of the tumour immune microenvironment AI-based image analysis, machine learning and deep
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. Research will focus on neural data integration, neural circuit modeling, biologically grounded representation learning, and foundation models for neurobiology. The Postdoctoral Fellow will work closely with
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multi-omics data and the use of machine learning and data science techniques. Strong publications record according to his/her career stage. Skills: Excellent programming and scripting skills, with deep
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associated with geography, soil sciences, hydrology, civil engineering, or related discipline, with research expertise in geospatial AI, deep learning foundation models, hydrology, river science. Candidates
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, labs, and clinical events Apply deep learning and transformer-based approaches to longitudinal EHR data Integrate multi-modal data (EHR, labs, vitals, imaging, etc.) • Position 3: Postdoctoral Researcher
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Details Title Postdoctoral Fellow in Neurobiology (Ponce Lab) School Harvard Medical School Department/Area Neurobiology Position Description Postdoctoral fellow in visual neurophysiology and deep
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Biology, Bioinformatics, Statistics, or a closely related discipline, and have an strong record of research productivity. The ideal candidate will have experience in deep learning, generative models
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disciplines associated with geography, soil sciences, hydrology, civil engineering, or related discipline, with research expertise in geospatial AI, deep learning foundation models, hydrology, river science
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-fellow-in-deep-learning-for-subsurface-imaging Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/290391/postdoctoral-research-fel… Requirements Research FieldComputer scienceEducation
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, or a related field. Proven experience in machine learning, deep learning, generative AI and data mining. Strong programming skills (e.g., Python, R, MATLAB, or similar). Experience with data