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methods to provide explainable outputs from AI models in presence of attacks on the models or data, and scalable methods that move beyond feature attribution aiming for root cause analysis and decision
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extensive epigenetic, genetic, and phenotypic data, applying cutting-edge analytic methods to uncover the biological underpinnings of mental health. You will contribute significantly to the Dunn Lab’s
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, or robot perception. Strong programming skills in Python and/or C++, with experience in robotic software frameworks (e.g., ROS/ROS2). Experience with machine learning or computer vision methods, preferably
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, we will apply interdisciplinary approaches in structural biology (cryo-electron microscopy, cryoEM; crystallography), biophysical and biochemical methods, as well as functional studies conducted
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. To this end, we will employ advanced molecular, cellular, and systems biology methods and tools, as well as various research models—from standard cell lines to primary lines and several mouse models
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. We expect applicants to hold a PhD in a relevant field such as techno-anthropology, science and technology studies, human-computer interaction, human-robot interaction, digital health, anthropology
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& Experience: • Experience with qualitative methodology and survey methodology • Experience leading research studies that center people with limb loss and limb difference Required Licensure/Certification
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wireless systems using the new channel sounding. Challenge 2: Different method for spectrum sharing need to be identified for potential deployment in networks and in network planning tools and modelling
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considering also the physical interactions between gesture and vocal production movements (e.g., breathing and articulation). The project looks at co-singing gesturing practices in three different vocal
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reporting requirements on AI for Health research and projects. Required Qualifications Ph.D. in Biomedical Engineering, Computer Science, Electrical and Computer Engineering, Integrated Systems Engineering