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Uppsala University, Department of Information Technology Are you interested in probability theory, statistics, and mathematical modelling? Would you like to develop new methods for uncertainty
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, micro-CT, particle size analysis, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a
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qualifications Experience in one or more of the following areas is considered a merit: data analysis using ROOT, particle-transport simulations using Monte Carlo codes such as Geant4, FLUKA, or OpenMC, nuclear
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motion in non-classical geometries using combinatorial, algebraic, and group-theoretic methods, inspired by the mathematical theory of articulated systems and constraint geometry. Possible tools include
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experimental and computational methods to identify molecular mechanisms leading to dysfunctional cellular states in human disease (www.camunaslab.org ). The candidate will contribute to the improve Slice-seq, a
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circulating tumor DNA, with comprehensive tissue-based profiling methods such as gene expression analysis, DNA sequencing, single-cell sequencing, and spatial transcriptomics. These high-dimensional data
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and statistical methods as part of a close collaboration between Uppsala University, Westinghouse, and Vattenfall? Would you like to contribute to the development of fast, robust and reliable
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fieldwork – in one or more infrastructure sectors (e.g. energy, water and sanitation, mobility or food) in European and Indian cities analyse the material using qualitative process methods (path tracing) and
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in teaching and student supervision corresponding to a maximum of 20% of full-time employment. Applicants should have experience with methods commonly used in biomedical research, such as mammalian
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peptidomics at Lund University. The duties include: Planning and conducting experiments. Developing and optimizing methods for sample preparation, peptide enrichment, and fractionation. Performing LC-MS/MS