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, repeatable coverage of fire-prone regions. When combined with modern statistical and machine-learning approaches, these data enable robust mapping of fuels, assessment of burn severity, estimation of biomass
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skills. Preferred Qualifications: Prior research experience in computational biology, mathematical modeling, or immunology. Familiarity with numerical methods, parameter estimation, and data visualization
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methods, parameter estimation, and data visualization. Some knowledge of probability and statistics. Other Requirements: CV Research Statement 3 Reference Letters Cover Letter Full-time, 12-month position
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to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures of health, well-being, and human
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learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted drug design” is led by Docent Juri Timonen
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 hours ago
Carolina, US Hiring Range $22.00 - $25.00/per hour depending on experience and qualifications Proposed Start Date 09/29/2025 Estimated Duration of Appointment 6 months not to exceed 11 months Position
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the combined themes of human-computer interaction and critical computing. The lab will be exploring the notion of "deceptive by design" on all fronts: social identity cues in the design of LLM-based chatbots
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studies and interactive AI systems. This position will be funded based on an initial 2-year contract + 2 years extension. The key idea is to apply theories, models, and methods from psychology to improve
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. Selection methods and criteria IV.1. Selection Methods: Assessment of scientific background and CV [ABC (90%)] and Interview [I (10%)]. IV.2. In theassessment of the candidate’s background and CV, scientific
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is to apply theories, models, and methods from psychology to improve Human-AI interaction. Your network and team The Aalto Engineering Psychology Group concentrates on research in human-AI interaction