77 cloud-computing-"https:" "https:" "https:" "https:" "https:" "https:" "St" "University of St" positions at University of Lund in Sweden
Sort by
Refine Your Search
-
Scientist to improve the data analysis experience within the MAX IV computing environments. The successful candidate will contribute to developing and supporting the overall software ecosystem for data
-
Doctoral student in development of nanowire devices for photonic neuromorphic computing (PA2026/472)
analysis. You will work on developing and exploring the synthesis, processing, properties, and performance of nanowire-based devices for nanophotonic based neuromorphic computing and optical sensing. Your
-
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
-
are united in our efforts to understand, explain and improve our world and the human condition. Description of the workplace Within the Centre for Analysis and Synthesis (https://www.cas.lu.se
-
systems, Applied AI/ML, Computer Security and Cryptography. The division runs several research projects through different large research collaboration platforms and arranges extensive workshops and seminar
-
upgrades / replacements of key RF components Qualifications Basic understanding of physics, electronics and electrical equipment Computer skills in excel and/or Matlab Fluent in written and spoken English
-
Department of Computer Science. The Graphics Group has a long history of internationally recognized research in the areas of Real-Time Rendering, Graphics Hardware and Ray Tracing. The Group has collaborations
-
/technology High school-level computer knowledge and technical interest. Experience and knowledge below are seen as merits: Experience with electronic hardware and understanding safety-compliance rules
-
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
-
integration into SasView. Required qualifications Ongoing university studies in physics, applied mathematics, computer science, engineering, or a related field Programming experience in Python Good