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the progression of ARDS in intensive care patients with sepsis. To enable this, we will develop information-theoretic machine learning methods to determine which protein interactions are driving disease progression
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statistical mechanics. The Computational Biochemistry group consists currently of eight coworkers and combines quantum chemistry, statistical mechanics and machine learning with biochemistry, medicinal
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from information and coding theory, machine learning, and distributed algorithms. The project is in collaboration with Linköping University, which includes opportunity for research visits. The project is
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students. The rest of your time (40%) is devoted to teaching. The department has developed several courses within data science, e.g., Bayesian methods, Advanced Machine Learning, Deep Learning and AI methods
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position as Senior Lecturer. Optimization, machine learning, and control theory together form a central toolbox for understanding, analyzing, and controlling complex systems. These fields span deep
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data at an internationally competitive level. Experience of biostatistics or machine learning approaches Proficiency in a scripting language like R or Python, as well as ability to work efficiently in a
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the design of antibody modalities Documented experience from cancer-related research Documented research experience in AI/machine learning/deep learning Documented experience in the development of therapies
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that are commonly used today. Using the improved noise models, machine learning methods will be used to enhance the segmentation of EEG data into auditory signal and background activity allowing for refined control
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, for that reason we are looking for someone who has: Documented research experience in the design of therapeutic antibody modalities Documented research experience in AI/machine learning/deep learning Documented
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10 Apr 2026 Job Information Organisation/Company Lunds universitet Department Lund University Research Field Psychological sciences » Cognitive science Educational sciences » Learning studies