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-of-the-art machine learning and computer vision methods and their applications Your Profile: Excellent Master’s degree in engineering, computer science or mathematics (or a related field), with a focus
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evaluation projects using qualitative, quantitative and mixed methods, and has a strong emphasis on collaboration, co-production, and impact. The Role We are seeking a Postgraduate Research Assistant to
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(spoken and written), certified if not a native language; e) Basic computer knowledge from the user's perspective; f) Show professional rigor and strong ability to work in a team; g) Demonstrate resilience
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structures and diagnostic targets. 3. Explainable AI Implementation Integrate XAI methods (e.g., Grad-CAM, Guided Backprop, SHAP) into the system. Generate and interpret visual explanations for model outputs
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methods to understand neuroendocrinologic mechanisms underlying risk vs. resilience for psychiatric disorders. The Clinical Research Assistant will work on studies examining psychopathology during
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Osteoarthritis (PTOA) is pervasive and represents a significant socioeconomic burden as it is estimated to result in expenditures on the order of 15 billion dollars per year within the United States civilian
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at international conferences and learn about state-of-the-art methods in machine learning, reinforcement learning and computer vision for the life sciences Your Profile: Excellent Master’s degree in engineering
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to 25lbs. Sitting for long periods of time at a computer. Shift 10-12 (flexible) hours per week. Job Summary Are you conversant in statistics? Are you Interested in mixed methods research, and/or
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sites and time periods. Use the newly developed tools to estimate key ecosystem and land-surface parameters, and compare the results against existing model–data fusion methods. Apply the improved
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computational methods, will be used to identify and validate promising candidates. Further design and engineering efforts will be utilized to optimize and port successful sensors into sensing platforms being