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Experience Appropriate PhD in a related field. Preferred Qualifications Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in the environment
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. QUALIFICATIONS PhD in Civil Engineering, Environmental Science, Computer Science, or a related field Research experience in hydrology, geospatial analysis, and machine learning Skills of scientific writing and
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driving simulators (e.g., CARLA, SUMO) or robotic simulation environments (e.g., Isaac Sim, Gazebo). Experience with ROS or ROS 2. Experience with PyTorch or other machine learning frameworks. Hands
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Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived experiences. Embracing
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. The preferred candidate will have a strong academic or industrial background in machine learning, trustworthy machine learning and AI, agentic AI, adversarial machine learning, graph-based learning, multi-domain
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an exciting opportunity to work at the intersection of geoscience and advanced machine learning. The associate will collaborate primarily with Professor Qian Yuan, focusing on integrating state-of-the-art
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Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived experiences. Embracing
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TAMU. Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in the environment. Knowledge of characteristics associated with mild cognitive
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languages such as R, Python, Matlab. Familiarity with software development best practices (e.g., unit testing, version control). Familiarity with inferential statistics and machine learning. Expertise in
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Education and Experience: Appropriate PhD in a related field. Preferred Qualifications: Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in