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We invite you to apply for a 2-year postdoctoral position in the area of hybrid AI, combining modern language models (LMs) with ontologies and knowledge graphs (KGs). The position is part of a newly
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on bioinformatics analysis of spatial gene expression data as well as other modalities (i.e. microbiome; metabolites, proteins) generated using the Spatial Transcriptomics (ST) method, Spatial metaTranscriptomics
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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of formulating them, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment
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collaborative research environment to analyze unique spatial data in an innovative manner. You will develop and perform cutting-edge bioinformatic analysis integrating different multiplexed spatial data, and gain
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, Norrbotten 971 87, Sweden Subject Areas: Geometric Analysis; Mathematical General Relativity; Differential Geometry Appl Deadline: 2026/01/31 11:59PM (posted 2026/01/12, listed until 2026/01/31) Position
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Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 46 000 students and 8 500 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition. The...
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and polarisation visual systems: mantis shrimp, water fleas, and firefly squid. These species have been chosen to probe the evolution of advanced visual capabilities such as colour and polarisation
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by The Kempe Foundations. Project description Machine learning and artificial intelligence have had a major impact on medical image analysis in recent years. While CT and MRI provide highly
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Biology, Department of Life Sciences, to develop intelligent systems that integrate metabolic modeling, omics analysis, and automated literature mining. About us The Department of Life Sciences conducts