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will use machine learning methods to develop affinity ligands. These methods have been transformative for protein design, allowing generation of novel proteins which can suit a precise need. In this 4
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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various environmental samples ranging from extinct and ancient animals to consumer food products. These fragments can be detected and analyzed using our specialized wet and dry-lab methods. The objective
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in technology driven life sciences. Lehtiö group is a translational group of scientists with a drive to improve human proteome analysis by developing new methods that can be applied to improve
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and functional diagnostic methods. These methods are used in everything from experimental research to clinical studies on patients and large-scale epidemiological studies on volunteers. In
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Uppsala University, Department of Medical Sciences Are you interested cutting-edge genomics technologies and eager to contribute to developing methods at the forefront of life science? We
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spectrum, in topics in virology and immunology, and currently specializes in computational biology focusing on developing methods and applications of deep learning for protein sequence and structure, as
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The Department of Biochemistry and Biophysics is seeking a Researcher and Head of Unit with experience in drug development for placement at the Biochemical and Cellular Methods Unit, Science for
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variability in risk factor susceptibility, treatment response, disease pathogenesis, and clinical diagnosis (biostatistics, machine/deep learning), ii) Investigating causal processes and disease mechanisms
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university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Biology-informed Robust AI Methods for Inferring Complex Gene Regulatory