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develop analysis pipelines to analyze high dimensional spatial and single-cell data of cancer and immune tissue from patients and pre-clinical studies and should have a strong background in both
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or other forms of appointment/assignment relevant to the subject area. Required skills: Strong background in aquatic ecosystem science Proficiency in GIS and analysis of long-term environmental data
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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sequencing, and with computer scientists at KTH in Stockholm, focused on developing scalable probabilistic machine learning techniques for online phylogenomic analysis and placement of DNA barcodes. You will
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to be awarded, a PhD degree or equivalent in biochemistry, cell or molecular biology, genetics or a related discipline. We are seeking highly motivated applicants with practical experience in
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Analysis, Image Analysis, Machine Learning and Computer Vision, as well as Mathematical Statistics, Probability Theory, and Mathematics Education. The degree courses lead to bachelor, master, and PhD degrees
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experimental and theoretical approaches. Requirements: Well-documented expertise in any of the following areas: next-generation sequencing data analysis (singe cell and spatial sequencing). PhD in
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communication skills in English. Strong skills in programming and data analysis. Track record of scientific publications in international peer-reviewed journals. Meritorious qualifications include: Experience
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Physics Division that hosts the Langhammer Group provides further relevant information. Who we are looking for We seek candidates with the following qualifications: A PhD degree in physics. An experimental
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dynamical systems theory, including differential equations, simulation techniques, state-space and input-output representations, time-delay embedding, and/or time series analysis from experimental data