Sort by
Refine Your Search
-
and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create globally leading computational and data
-
. The PhD position is within the Data-driven life science (DDLS) Research School. DDLS uses data, computational methods and artificial intelligence to study biological systems and processes at all levels
-
life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health
-
applicant must have passed courses within the first and second cycles of at least 90 credits in either, a) Chemistry/Molecular Biology/Biotechnology, or b) Computer Science/Mathematics/Physics and at
-
) Computer Science/ Mathematics/Physics and at the second cycle level, 60 credits in Life Science, Computer Science Mathematics, Physics or Bioinformatics including a 30 credit Degree Project (thesis). Additional
-
) Computer Science/Mathematics/Physics and at the second cycle level, 60 credits in Life Science, Computer Science Mathematics, Physics or Bioinformatics including a 30 credit Degree Project (thesis). Selection
-
, probability theory, etc) A competence in quantitative topics equivalent to a mathematics, statistics, physics, computer science, or engineering degree is required (if your degree was not in one of these domains
-
) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
-
substantially equivalent knowledge in some other way. For this position, the applicant must hold a master’s degree in molecular biotechnology, bioinformatics, computer science, or another area that the employer
-
. To meet the general entry requirements for doctoral studies, you must: Hold a Master’s degree in computer science, image analysis and machine learning, engineering, data sciences, applied mathematics