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to mastering the great challenges facing society today. At the Institute of Radiopharmaceutical Cancer Research scientists (f/m/d) from the fields of physics, chemistry, biology, pharmacy, immunology, medicine
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bottleneck in the screening process. This PhD project will address this through deep integration of scanning probe electrochemistry, optical microscopy and machine vision, to develop a system that can
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development projects, and drive science forward. This position is one of several industrial PhD roles funded by the DDLS program, which supports training in four strategic areas: cell and molecular biology
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peptides, including the design of de novo sequences based on the elucidated mechanism. The first step will be to develop a computational approach to determine the critical peptide properties required
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 2 months ago
This is a fully-funded 4 year PhD offering an annual tax-free stipend of £20,780, tuition fees and an enhanced research and training grant. This PhD is one of a number of projects hosted by
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of the project is to 1) develop computational pipelines for image analysis and physical analysis of cell shape trajectories, and for combined morpho-molecular analysis of cell shape together with molecular markers
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postdoc in the lab. You have: A Master’s in Life Science, e.g., Molecular Biology. Expertise in functional genomics approaches and computational data analysis. Expertise and interest in gene-regulatory
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fees per semester in EUR None Combined Master's degree / PhD programme Yes Joint degree / double degree programme No Description/content The International Max Planck Research School for Biology and
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life. The successful candidate will work closely with experts in food allergy, neuroimmunology, gut physiology, and computational biology to characterize immune cell responses, construct spatial maps
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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