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modeling. Experience in cell culture, molecular cloning, and bioinformatics analyses is required. Proficiency in statistics and programming are highly meriting, especially in gene regulatory networks
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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biopesticide development and targeted antimicrobial delivery. The team is interdisciplinary, with expertise in molecular microbiology, structural biology, bioinformatics, and protein engineering, and currently
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responsibilities include bioinformatics analyses with a strong focus on single-cell RNA sequencing and next-generation single-cell barcode lineage tracing, as well as the interpretation of complex biological
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for the position will be important factors in the selection process. Additional useful qualifications Since appointment as a postdoctoral researcher is a career-development position for junior researchers, we
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. The project is conducted in close collaboration with researchers in mathematics, ecology, and bioinformatics. The fellow will be offered affiliation and a workspace at IceLab – the Integrated Science Lab
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computational and statistical methods, with demonstrated experience in reproducible and scalable bioinformatics environments. The applicant will work in close collaboration with other Engblom lab team members who
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new systems with bioinformatics, validate them in microbiological assays and then characterise the mechanisms of defence on the molecular level. Currently the lab is working on many (>10) novel, as-yet
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, as well as handling bioinformatics tasks such such as running analysis pipelines, performing quality control, and conducting downstream data analyses. You are expected to actively contribute to method
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bioinformatics, physics, statistics, computer science, computational biology, or related fields. Experience programming in Python (or R) as well as bash/shell scripting. Experience with machine-learning and deep