16 condition-monitoring-machine-learning Postdoctoral positions at University of Lund
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breakthroughs in deep learning–powered protein design, recognized by the 2024 Nobel Prize in Chemistry, have enabled the creation of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and
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using genetic data from family-based studies as well as -omics data for integrative deconvolution and machine learning methods for prognosis and therapeutic biomarker development. The collaborative
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empirical and ethical perspectives in research on forced migration. A central question is how faith-based organisations practice justice, i.e. what are the conditions, constraints and consequences
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processing (first, second and multilingual); multimodal language processing and learning; developmental language disorders; educational linguistics and language teaching, testing and assessment; and language
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standardized common-garden conditions. The work also includes investigations of the heritability of phenotypic traits that enable thermal adaptation, and may involve studies of the associated molecular and
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more information on our research website . We care about creating a positive, respectful, and stimulating environment. We value communication and collaboration and a workplace that promotes learning and
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learning–based protein design, for the successful design of 2D lattices. These methods will then be applied to generate designs targeted for experimental evaluation. Work duties The main duties involved in a
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good conditions for a balance between work and leisure. Read more on the university's website about being employed at Lund University, Work with us . About the employment This is a fixed-term employment
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to no more than 20% of working hours. The position includes the opportunity for three weeks of training in higher education teaching and learning. The purpose of the position is to develop the independence as a
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learning. Detailed description of the work duties: Conduct field sampling of bumblebees in central and northern Sweden. Morphological quantification of bumblebees in museum and field collections. DNA