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Field
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learning including reinforcement learning, nature inspired algorithms, deep learning, agent based modeling, and natural language processing. We are specifically interested in research focused
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, particularly within digital trials or real-world data studies. Expertise in analysing complex digital health data, including wearable sensor data, mobile health survey, and electronic health records. Downloading
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document algorithms to detect and quantify disease-relevant patterns. • Contribute to both in-house and open-source software initiatives. Research Communication & Collaboration (20%) • Assist with
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, and treatment across the lifespan Digital behavioral health interventions integrated into primary and specialty care Wearables, sensors, or digital biomarkers for remote patient monitoring and early
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to accelerate evaluation of costly simulations Genetic algorithms and other evolutionary techniques to generate a diverse set of high-performing solutions. You will design and implement new optimization
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and electronics hardware and firmware to develop optimized wearable sensor prototypes. At direction of faculty investigator, conduct biomedical optics experiments including imaging, sensing, wet lab
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. Applicants should have strong expertise in computational analysis of electrophysiological data as well as proficiency in large language models and machine learning algorithms. First-hand experience in
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or associate professor level in computer engineering, with desired emphasis in areas such as cybersecurity with a focus in system security or hardware security, internet-of-things, sensor systems, mobile
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Bachelor's degree in a technical field with 5+ years' experience in startup company formation and financing as CEO or CTO, in the technology sector, such as sensors, electronics, photonics, sustainability and
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for long-term production projects including large arrays of full-recticle and wafer-size semiconductor sensors, as well as one-off R&D pieces and small commercial activities requiring a rapid turnaround