18 computer-processor-phd-"https:"-"Institut-Agro-Rennes-Angers" Postdoctoral positions at University of Lund
Sort by
Refine Your Search
-
research area MERGE (https://www.merge.lu.se ), focused on climate modelling. Aerosol research has been conducted at Lund since the 1970s and is now a designated profile area at LTH (https://www.lth.se
-
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
-
position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position. The certificate proving the qualification requirement is met must be
-
technologies. The target chips include digital signal processors, radio frequency and millimeter wave frontends, data converters, as well as larger systems with a mixture of analog and digital signals. Our
-
. Merits for this position: PhD acquired within three years of last application date. Documented pedagogical experience. Experience in image analysis and/or computer vision, especially in the context
-
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
-
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
-
wider society. Administration related to the work duties listed above. Qualification requirements Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree
-
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
-
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