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molecular biology with a focus in genetics or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses. Alternatively, you have gained corresponding knowledge in
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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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multiple subfields represented, including animal behaviour, evolution, ecology, genetics, zoology, conservation, microbiology and animal welfare. See: https://liu.se/en/organisation/liu/ifm/biolo
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corresponding knowledge in another way. A successful candidate should have excellent study results and a strong background in mathematics. The applicant should be skilled at implementing new models and algorithms
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research, undergraduate and postgraduate education within the field of biology, with multiple subfields represented, including animal behaviour, evolution, ecology, genetics, zoology, conservation
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cancer. The goal will be to find genetic prediction models to be able to predict which childhood cancer patients have a high or low risk of toxicity in childhood cancer. Preliminary the doctoral project
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm