72 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S"-"TCAT-Dickson" positions at University of Lund
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equality and diversity as a strength and an asset. Your team, work duties and areas of responsibility The MAX IV Scientific Data group develops and supports software projects for data acquisition and
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difference! For further information, please visit: https://www.lunduniversity.lu.se/about-lund-university/work-lund-university www.sweden.se https://www.maxiv.lu.se/about-us/careers/compensation-benefits/
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a doctoral student at LTH on lth.se. Subject description This project aims to develop novel algorithms for Neural Rendering for Computer Graphics and Real-Time Rendering. By using ANNs, coded for high
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actor networks and impacts on smallholder farmers in the Global South". The project examines which actors that farmers become connected to through participation in “carbon farming” programs, and how data
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breast cancer risk prediction models to support individualized screening. Data will be drawn from the Malmö-Breast ImaginG database and linked with additional transcriptomic and clinical datasets. Data
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its web server for comparative genome analysis, developing Python-based tools and code for retrieval and processing of publicly available genomic data, and participating in the analysis of microbial
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sequencing, and bioinformatics analysis of data from large-scale sequencing, including single-cell sequencing data. DNA and RNA extraction, PCR, cell culture, and working with experimental animal models
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1-2 Season employed fieldassitants by the Department of earth and enviromental science. (PA2026/808)
weighing them, and estimation of some plant specific traits. The data will be used in analyses of remotely sensed data for crop monitoring, and any collected data will be made available to the assistant
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that the applicant has a PhD in Biology, Ecology, Data Science, or a related subject, or an international degree deemed equivalent to a PhD, within the subject of the position, completed no more than three years
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, the project employs a mixed methods approach, integrating actor-network mapping, interviews, extended case studies and participatory visual methods. By combining a global mapping of key actors, data flows