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and documented background in machine learning, deep learning, data analysis and programming. Previous experience in research and knowledge in bioinformatics, biophysics, biochemistry, molecular biology
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and/or functional imaging or application of computational modeling, machine learning and AI to understand cellular function. At least five years’ experience working within the university system, another
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, acquired recently (mainly within the last five years), and show a reflective approach to student learning and their own role as a teacher, and thus be competent to teach preclinical pharmacology. Furthermore
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administrative support systems Solid computer skills and proficiency in Microsoft Office (including Excel), and the ability to adopt new digital tools is required. Fluency to express yourself in speech and writing
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. The project explores the role of tumor-promoting inflammation in cancer progression through bioinformatics-driven, machine-learning and multi-omics analyses integrated with experimental data. Ideal candidates
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of small cryptic plasmids in the development and spread of antibiotic resistance, and ii) Use machine learning tools to examine the complex interplay between bacterial hosts, various plasmids and resistance
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will find yourself in a team that values creativity and allows you to influence the decisions made within the group. Furthermore, we value continuous learning and encourage you to allocate time for
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managing large amounts of data by designing structured databases (PostgreSQL, MySQL). Machine learning methods such deep learning for analysis of proteomics data and classification of cancer profiles. Since
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circumstances apply, this training for teachers in higher education may be completed during the first two years of employment. Documented ability to teach in Swedish or English is a requirement unless special