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the PI or another team member per year. Organise and participate in the international conference and contribute to the editing of the resulting volume. Teach or co-teach (up to 10% of annual workload
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to the editing of the resulting volume. Teach or co-teach (up to 10% of annual workload). Contribute actively to the project and the host institution’s research community. Eligibility and assessment Applicants
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decade, providing opportunities to mine big data to learn more about the drivers of AMR in humans. Our work includes computational analysis of antibiotic resistance and microbiomes, statistical analysis
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biology, biomolecular, and biohybrid materials. Requirements Recently obtained PhD (within five years) in biotechnology, molecular biology, biochemistry, or a related field. The candidate should have sound
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motivation to learn new skills. Familiarity with a mathematical programming language (e.g., Matlab, Mathematica) is preferable but not essential. Independence and problem-solving skills. There is flexibility in
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specifically developing and applying new technologies (e.g. mixed reality, movement- and biosensing, remote cognitive testing, mobile EEG) for studying neurodevelopmental disorders (e.g. ADHD, autism, learning
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learning. You will be working in the research group of one of the PIs of the projects, but in collaboration with the others. The PIs are Talayeh Aledavood, Juhi Kulshrestha, and Mikko Kivelä. About the
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participate in a project which investigates and develops novel immunotherapies (cell therapies) to cancer, utilizing both mouse and human systems. Applicants should possess a PhD degree or be close to
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data has increased massively in the last decade, providing opportunities to mine big data to learn more about the drivers of AMR in humans. Our work includes computational analysis of antibiotic
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. The concept has lately gained increasing interest from researchers in applied mathematics and machine learning. This is due to its remarkable flexibility, mathematical elegance, and as it has produced state