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be in close collaboration with experimental and clinical collaborators and will provide resources for large-scale data generation and full access to the latest long read sequencing technologies
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the financial sector and the economy at large. This role is ideally suited for those wishing to work in academic or industry research in quantitative analysis, particularly in the area of machine learning and
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in this position will conduct/lead applied as well as fundamental research in physics-informed Artificial Intelligence (AI) and Machine Learning (ML) methodologies enabling digital twin functionalities
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may include but are not limited to: algorithm and software development; application or development of computational or statistical methods; data analysis; modeling; statistics and machine learning
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motion capture systems and wearable sensors Engage with large-scale, longitudinal analyses of biomechanical data following limb trauma and amputation in the military Participate in efforts to develop novel
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the last 5 years or soon to be completed. Demonstrated experience in building machine learning/deep learning models using one or more large scientific data sets involving sequence, protein structures
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researchers and graduate students. Required Knowledge, Skills and Abilities AI/ML Expertise: Strong knowledge of advanced machine learning, deep learning, and AI techniques. Programming Skills: Proficiency in
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quantitative data analysis: applied machine learning, statistical analysis, and handling complex data. Programming skills in Python and R are essential Experience in applying computational methods to research
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have exceptional resources to facilitate research including access to administrative, research, and computer support staff. Required Qualifications* PhD degree or equivalent in epidemiology, gerontology
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area of expertise. You may be a great fit if: You are a passionate researcher with a PhD in Computer Science or a related field, experienced in machine learning for spatial data management, with a track