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others, gained through research, academic, or applied settings Experience applying machine learning, natural language processing, or other computational methods to health, biomedical, or research problems
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methods that combine soundscape targets, acoustic metamaterials, physical modelling, inverse design, machine learning and perceptual evaluation. The postdoc will develop models and design methods
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for the production of architectural spaces; therefore, extensive computer skills, as well as in-depth knowledge of design-related software such as Rhino, Grasshopper, Blender, Unity, AI applications and laser scanning
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fluid mechanics, computational geometry, meshing, computational graphics, computational vision, or scientific machine learning in general. Successful candidates will join a community of researchers in
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world-class, mission-driven programs. Staff at the Lab teach undergraduate courses, advise graduate students, collect and disseminate world-famous digital resources on biodiversity, and engage with
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) and hardware integration. Knowledge of machine learning, reinforcement learning, or vision-language models for robotics is a plus. Hands-on experience with robotic arms (e.g., UR5, Franka Emika
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chip packaging F5 Experience using data analysis or machine learning tools for electronics reliability or sustainability assessment F6 Experience with rapid prototyping technologies (3D printing, laser
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boson decays, searches for supersymmetry and other new phenomena, and measurements of rare standard model processes. We vigorously pursue the use of machine learning techniques for data analysis
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packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process adaptive and scalable. The research effort will be directed towards the selective recovery in
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learning and deep learning. Specific Requirements PhD in acoustics. Knowledge of acoustical measurement techniques, as well as physical acoustics. Some experience in acoustic signal processing and machine