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Natural History. The researcher will develop deep learning models to predict individual bee age based on wing morphology. This model will be trained of existing wing images and applied to images of museum
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integrates neuroimaging, sleep measurement, digital phenotyping, electronic health record (EHR) data, and deep clinical phenotyping to identify predictors of symptom trajectories and functional outcomes in
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. scRNA‑seq, scATAC‑seq). Train, evaluate, and benchmark deep learning models operating on single‑cell, regulatory, or multimodal biological data. Support target and mechanism prioritization by integrating
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development. You enjoy supervising and teaching and using your excellent communication skills to inspire the coming generation develop the same deep passion you have for quantum technology. You always have an
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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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Frankfort, KY Grade Level 50 Salary Range $81,640-138,798/year Type of Position Staff Position Time Status Full-Time Required Education MA Click here for more information about equivalencies: https
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host chromatin pathways (DFG Research Unit DEEP-DV, FOR5200). The group uses experimental infection systems, an array of high-throughput sequencing methods, and single-molecule live-cell imaging
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communication skills. Proficiency in developing deep learning models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in
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neurological disorders, novel applications of deep brain stimulation technology to the treatment of neurological and psychiatric disease, the mechanisms of deep brain stimulation and finally motor and reward
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with experience in clinical social work to teach required MSW practice courses and other courses (as needed) in our MSW program. This is a 9-month position that teaches the equivalent of six courses