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. Demonstration of open source project work (e.g., GitHub repositories), and familiarity with machine learning and deep learning frameworks (scikit-learn, PyTorch, LLM API’s) is a plus. Applicants should
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of peptide design and chemistry, computational methods (machine learning, deep learning, genetic algorithms), microbiology, synthetic biology, and related areas essential to developing novel
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on: • In-depth expertise in reliability testing of wide bandgap (WBG) technologies • Deep knowledge in in-situ measurement techniques for WBG technologies • You work on developing hybrid prognostic
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Are you looking for a PhD position where you develop state-of-the-art machine learning methods for the life sciences (geometric deep learning, transformer-based approaches, ...) with a focus on
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key regulators of inflammation and tissue remodeling in gut and skin diseases. • Apply and refine AI/ML methods, including deep learning, neural networks, and interpretable models (e.g., SHAP, BioMapAI
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We are seeking a highly motivated PhD candidate with a strong interest or background in AI as well as in one or more of the following areas: Generative AI, Natural Language Processing, Deep learning
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the Infrared sensors are working in overlapping field of view The Person (Essential) Knowledge, Skills and Experience Track record of design, deployment and evaluation of machine/deep learning-based techniques
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the challenge of time-consuming sideshaft testing. As a key member of the team, you will apply cutting-edge machine learning and deep learning techniques to dramatically reduce testing cycles. You will lead life
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-dimensional variable selection, longitudinal and survival analysis, machine/deep learning, bioinformatics methods in -omics data are preferred. Demonstrated evidence of excellent programmin g, collaboration
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Join a dynamic team of motivated individuals with deep collective experience throughout digital forensics, incident response, investigation, operations, and academic research. We seek individuals