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incorporate it into mathematical models of trait evolution across phylogenies. The work combines dimensionality reduction and geometric data analysis with the development of statistically rigorous comparative
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methods for analysis of cellular and molecular biology data. The host institution, The Department of Gene Technology , is the most prominent research environment at KTH, according to bibliometrics
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processes. Projects can include assembling, sharing, integrating, and advanced analysis of large amounts of data from diverse sources, including experiments, observations, and simulations, to gain a deeper
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biomarkers in body fluids. We are seeking a data scientist dedicated to clinical proteomics and biomarkers discovery and validation studies. This role will focus on building robust data management and analysis
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analysis of such data will thus be a core activity in the doctoral program. Furthermore, performing flow cytometry analyses and cell sorting will be central and also immunological assays will be used
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credits, or Mandatory requirement for English equivalent to English B/6 Experience in formulating lipid nanoparticles with mRNA via microfluidics Experience in sample preparation and data analysis from
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previous experience in mass spectrometry, including high resolution mass spectrometry. Additional experience in raw data pre-processing and nontarget analysis applied to environmental research, metabolomics
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perturbation-based GRN inference for single-cell and spatial multi-omics data, to boost GRN quality and add the cell type and tissue heterogeneity dimensions to causal regulatory analysis. A deep learning
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Comprehensive skills in data analysis and bioinformatics Proficiency in programming with Python Proficiency in version control (Git, GitHub) Meriting criteria are: Experience in mechanistic and ODE-based
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A position as Associate Senior Lecturer/Assistant Professor (tenure track) within the area Data-Driven Evolution and Biodiversity in aquatic or terrestrial environments is open at the Swedish