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explainable AI for large-scale and complex datasets by developing algorithms, pipelines, and tools suitable for critical decision-making contexts. The doctoral student will be based at the Health Technology
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of algorithms, data structures, high-performance computing, machine learning and microbiology. The position at the Department of Molecular Biology at Umeå University is temporary for four years to start
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healthcare, in most cases, there is only access to information at the patient level, about the patient’s health status and disease development. In this project, we will develop theory, algorithms and methods
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(Spatial VDJ). Using established and newly developed algorithms, we map B cell evolution within tissues, including class switching and somatic hypermutation, and identify putative candidate tumor-regulatory
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will focus on developing theoretical and algorithmic foundations for goal-oriented, semantics-aware communication enabling timely and reliable cloud-to-agent interactions. For more details on semantic
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and perspectives lay the foundation for learning, creativity and development. We welcome people with different backgrounds and experiences to apply for the current employment.
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of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test software tools, and
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look forward to receiving your application! Do you have a background in machine learning and interested in telecommunications? You have a chance to contribute to development of sensing methods for new
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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positions in the interdisciplinary research environment “Culture and Society” to develop research on themes relevant to the thematic area “Digital Society, Infrastructure, Legacies”. This thematic area