20 parallel-and-distributed-computing-phd Postdoctoral positions at University of Lund
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Information Technology conducts broad research in cryptography, computer security, wireless and wired networks. The Security Group has around 20 members. The main research areas are cryptography, privacy, and
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qualifications: PhD degree in computational science, computational biology, or equivalent Master’s degree in biomedical engineering or equivalent Experience of using various data sources (radiological images
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Information Science (GIS), and computational science for health and environment, to study processes spanning from the microscopic to the planetary, across all time scales. The Inverse Modelling group at the Department
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cluster is part of The Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society (WASP-HS), which is a national research program in Sweden. The vision of WASP-HS is to foster novel
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of bachelor and master degree projects. Qualification requirements Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within
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, computer science, medical physics or other field relevant for the project. The PhD degree must be completed no later than at time the employment decision is made. The ability to develop and perform high-quality
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to this research. You are expected to attend project meetings and present results at scientific conferences. Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree
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molecular structures capable of transferring electrons and interacting with light. Such assemblies also have applications in biomedicine. The primary objective is to develop computational methods, using deep
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accordance with departmental requirements. Qualifications Applicants must have obtained a PhD degree in the social sciences, preferably in sociology of law, sustainability science, anthropology, sociology
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strategies. The research group focuses on exploration of tumor immune microenvironments through spatial omics and imaging, development of computational models for prediction of molecular and clinical features