-
year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
-
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
-
bioinformatics, engineering physics, molecular biology, computer science, or a related field. You should have strong programming skills (e.g., in Python or R) and a keen interest in applying data-driven methods
-
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
-
, 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
-
vetting. If security vetting is conducted, the applicant must pass the vetting process to be eligible for employment. Please do not send offers of recruitment or advertising services. Submit your
-
, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab
-
. If security vetting is conducted, the applicant must pass the vetting process to be eligible for employment. Please do not send offers of recruitment or advertising services. Submit your application through