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An exciting opportunity has arisen for a talented computer scientist to join our team as a researcher within the Green Algorithms Initiative in the Department of Public Health and Primary Care, one
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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supervisors, from different universities: Dr. Georgios Tsaousoglou at DTU, and Dr. Maryam Kamgarpour at EPFL, Lausanne, Switzerland, with the opportunity to undertake an extended research stay at EPFL. Project
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efficient and scalable algorithms that can handle large-scale datasets. Tensor Analysis: Analyze the structure and properties of multidimensional networks represented as tensors. Investigate different
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, transcriptomics (bulk, scRNAseq) epigenetic profiling (methylome, Atac-Seq, Chip-seq) and proteomics, using computational methods. Algorithm Development: Designing and implementing algorithms to process, analyse
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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computational tools, pipelines, or algorithms to improve the accuracy and speed of genomic workflows, particularly for rare variants and noncoding regions. • Functional Follow-up: Implementing functional assays
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on using unstructured and overset meshes with high-fidelity algorithms to obtain scale-resolved data. Candidate will also post-process data using data-driven and physics-driven methods to extract fundamental
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implementation of algorithms to analyze the data and integrate with other data sets including clinical outcomes data. This person will also help with the generation of tools needed for manipulating and preparing