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the university/college community, and apply for jobs. Minimum Qualifications PhD in human-computer interaction, information science, learning sciences, computer science, or a related field, conferred by the start
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strong programming, experimental-design, and quantitative-analysis skills Have experience working with large-scale data, machine-learning models, human-subject studies, platform audits, or computational
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biological domains is a must PhD in computational biology, computer engineering, computer science, (bio)statistics, artificial intelligence, physics, or related. Desire to push the frontier
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collection, data engineering, statistical modeling, or computational text and image analysis; Machine learning, natural-language processing, large language models, or evaluation and auditing of AI and online
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before starting—in computer science, electrical or computer engineering, information science, or a closely related discipline. Less than 5 years post receiving the Doctoral degree. Meet the mandatory
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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/or oceanography; or experience working with numerical simulations, large data, scientific programming, and/or machine learning. Applicants are asked to send a CV, a brief statement of research
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framework to train, test and validate a machine learning-based forward operator to enable the assimilation of SAR data into a crop growth model. Be responsible for the curation, storage and maintenance
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field of research Participate in education, and PhD and master student supervision Profile Strong background in computational biology, bioinformatics, machine learning, or a related quantitative field
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equivalent foreign degree, obtained within the last three years prior to the application deadline Experience with simulation frameworks, system-level performance evaluation, or machine learning, is highly