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We have the power of over 40,000 students and co-workers. Students who provide hope for the future. Co-workers who contribute to Linköping University meeting challenges of today. Our fundamental values rest on credibility, trust and security. By having the courage to think freely and innovate,...
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interpretation of results. You will also tailor these analyses in response to clinical and researcher feedback, and help develop new algorithms where needed: this may include the incorporation of genomic or other
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with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
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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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qualifications You have graduated at Master’s level in Biology/Medical Biotechnology/Genetics or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses Biology/Genetics
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physiology and ion channel pharmacology is a must, which includes experience of the use of electrophysiology to provide mechanistic insights into how endogenous modulators and genetic variants affect ion
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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
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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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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