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aspects of the energy transition through quantitative analysis of future potential for flexible energy use on Gotland based on different scenarios of diffusion of energy technologies in the energy system
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and analytical skills, cultivate independent critical thinking, and formulate research questions with scientific rigor. Learning activities will include data processing and analysis using various
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available at the Chalmers Materials Analysis Laboratory (CMAL) as well as at international large-scale research infrastructures such as synchrotrons and neutron sources. The project is led by Dr. Chiara
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will be entirely computational, focusing on the large-scale bioinformatic analysis of proteome data from a wide range of existing species. The research will focus on understanding mutational robustness
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. Candidates are further expected to have experience in processing and analyzing high-throughput genomic sequencing data and in statistical analysis. Previous experience with Drosophila melanogaster or other
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, and will apply deep learning to integrate the analysis flows. The PhD student will develop the method and apply to numerous in-house samples of environmental sequences, pushing the boundaries of RNA
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disorders/addiction, particularly relevant is experience regarding stress models and operant self-administration. Have special knowledge in behavior analysis (using software programs such as EthoVision), and
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previous experience with e-graphs, or is familiar with theory and algorithms used by, for example, proof assistants, term rewriting systems, optimizing compilers, program analysis tools, constraint solvers
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environmental stresses, plant growth and development, biotechnology and metabolic engineering, regulation of gene expression, population genetics, genome analysis, and the development of breeding systems. Species
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researchers at various academic levels. The group has a strong focus on epidemiological studies that involve large datasets and often require advanced study design and analysis. The research group leads