Sort by
Refine Your Search
-
, spatially aware QC, normalization, cell segmentation integrating H&E imaging and transcript density, and spatial domain identification Single-nucleus integration and annotation: large-scale multi-sample batch
-
are looking for an Industrial PhD Student to join an ambitious project focused on building foundational models of human biology using large-scale, multimodal data. In this role, you will work at the
-
· Develop and apply transformer-based foundation models and machine learning methods for large-scale epigenetic datasets · Integrate longitudinal data and biological prior knowledge into AI models · Actively
-
will engage with large-scale longitudinal health data, develop and validate computational models, and contribute to methods that will enable pathogen-resolved population research across the lifespan
-
symptoms emerge. The group combines large population-based and twin cohorts with longitudinal blood-based biomarkers, multi-omics data, and advanced epidemiological methods. The group is part of the research
-
is enabling major advances in clinical pathology and cancer diagnostics. Today’s AI methods require large amounts of data with a detailed ground truth annotation that the AI system can learn from. In
-
data-driven diagnostics. About the project Cancer treatment often involves surgery, chemotherapy, and radiotherapy. While these treatments have improved outcomes, they can be long-lasting and cause
-
of the central open questions in biology. This project aims to address this challenge using cutting-edge AI and large-scale multimodal data. We are recruiting a PhD student for the project: “The code that shapes
-
transformation and large green investments in northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition
-
by developing data-driven approaches to identify and prioritize isoform-specific therapeutic targets, enabling a new level of precision in RNA-based treatments. The project will combine large-scale