Sort by
Refine Your Search
-
. General Description of the DDLS Program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
-
information about us, please visit: the Department of Biochemistry and Biophysics . About the DDLS PhD student program Data-driven life science (DDLS) uses data, computational methods and artificial
-
personnel from all different sites at the NBIS retreat. Requirements You should hold at least a bachelor’s degree in computer technology, computer science, systems science or possess documented equivalent
-
university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Biology-informed Robust AI Methods for Inferring Complex Gene Regulatory
-
equal opportunities for all. Further information about the position can be obtained from the Assistant Professor, Emil Marklund, emil.marklund@scilifelab.se . Application Apply for the position
-
stakeholders at all SciLifeLab sites in Sweden, e.g. representing the technology platforms, the national data centre, the operations office, the training hub, the data-driven life science (DDLS) research program
-
Skłodowska-Curie Actions (MSCA) Cofund postdoctoral program, that will train 48 future leaders in life sciences. It runs 2025-2030 with a budget of 6,88MEUR. About SciLifeLab SciLifeLab (Science for Life
-
Program for Data-Driven Life Science (DDLS ) and the student joins its research program . Supervision: Associate Professor Hossein Azizpour What we offer Admission requirements To be admitted
-
science more generally with managing data, software, tools, and support on nationally and internationally available computational resources, including the new AI Factories and EuroHPC resources, at NAISS
-
, molecular biology, computer science or related subjects the employer considers of relevance to the position Experience (3+ years) in working with advanced bioinformatics analyses of omics data from high