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- NEW YORK UNIVERSITY ABU DHABI
- Carnegie Mellon University
- Aarhus University
- CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences
- Cornell University
- EPFL
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- MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE
- Mohamed bin Zayed University of Artificial Intelligence
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- VIB
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Field
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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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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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depth in some of the following areas (not all are required): Large-scale data analysis and learning analytics methods Experimental or quasi-experimental design; validity and measurement Working with LLMs
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data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining, including XAI, as well as for data access and query processing. Aarhus
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, established track record of publications in computational microscopy, computer vision, or parallel machine learning Adaptability: A demonstrated, strong willingness to learn and bridge the gap
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM