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deadline is 30 July 2025. Work task You will provide researchers with expertise in the planning and performance of electron microscopy (EM), electron tomography and image analysis, in medical, biological
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genealogical relationships and genetic divergence across species, but its complexity requires new methodologies for efficient analysis. This project aims to use Variational Inference (VI) methods, enhanced by AI
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collaborative project at the division of Biophysics, Department of Applied Physics, KTH. The goal of the project is to use microscale acoustofluidic technology for the formation, development and analysis of 3D
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evolutionary analysis. A central component of the research will be to develop machine learning and deep learning methods trained on coding sequences and protein structure to extract patterns in data and to draw
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tasks include development of adequate single-molecule labeling strategies, optimized use of high-precision MINFLUX microscopy, and establishing methods for data precision analysis. What we offer A
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to the delivery capability of lipid nanoparticles. Bulk techniques (e.g. small angle scattering) will be coupled with single particle analysis to improve our understanding of how disease impacts the performance
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or advanced statistical methods, to help explore molecular, imaging, clinical and/or epidemiological data. You will apply, adapt and develop machine learning approaches to provide data analysis support to data
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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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at midnight, CET/CEST (Central European Time/Central European Summer Time). Applications must include the following elements: CV including your relevant professional experience and knowledge. Application letter
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part of our dynamic team, you will work closely with researchers to process large-scale biological data and contribute to advancing our data analysis infrastructure. Strong problem-solving skills