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The Rosen Research Group at Princeton University (https://rosen.cbe.princeton.edu) is searching for a postdoctoral or more senior researcher interested in computational materials design and
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capabilities, leveraging high-throughput experimental data to connect genotype to community-level function. Responsibilities could include: · Develop novel computational, hybrid, and deep learning models
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
historical insights and to develop reusable computational workflows for semantic modelling in premodern corpora. Job description The successful applicant will be affiliated with Work Package 1: Semantic
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systems, advanced sensing technologies, application of deep learning and AI for wireless systems, etc. For more details, please view: https://www.ntu.edu.sg/eee We invite applications for the position
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the area of the AI Computer Systems. The successful candidate will lead an innovative research program in cutting-edge AI computer system technologies. The position requires knowledge of both hardware and
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Job Status Full-time Hours Per Week 40 Offer Starting Date 1 May 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Plasmacytoid Dendritic Cells during HIV-1 or HIV-2
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to study cancer evolution, including developing CRISPR-based molecular recording tools to track tumor evolution history, modeling tumor progression using genetically engineered mouse models, applying single
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funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 207 / 2026 / 1877 Is the Job related to staff position within a Research Infrastructure? No Offer
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Shankland Lab group to analyze high-throughput data sets related to the kidney in the settings of pre-clinical models of disease and aging. Specifically, the lab utilizes transcriptional profiling approaches