Sort by
Refine Your Search
-
: have experience working on machine learning systems in PyTorch or JAX have experience in interpretable methods in machine learning have experience in using version control systems like Git and public
-
knowledge in microbial ecology or ecology. You should show a keen interest in learning machine-learning and other AI methods. The working language is English and excellent communication skills in English
-
, and statistic are merits as well as documented knowledge in microbial ecology or ecology. You should show a keen interest in learning machine-learning and other AI methods. The working language is
-
another way. If you can say yes to some of the below points it is highly beneficial: Proficiency in programming languages, preferably Python. Knowledge of AI and machine learning techniques Experience in
-
environment, and, preferably, previous experience in working with machine learning and/or artificial intelligence. Good presentation and communication skills in oral and written English are also required
-
environment, and, preferably, previous experience in working with machine learning and/or artificial intelligence. Good presentation and communication skills in oral and written English are also required
-
strong focus on developing machine learning tools and novel molecular representations. Fundamental knowledge of machine learning and programming as well as molecular biology is necessary. The tools
-
modelling, machine learning and computational approaches in biodiversity science. The student will be will be supervised by Aelys Humphreys (Stockholm University) and work closely with an international team
-
, mathematical modeling of dynamical systems, and machine learning is advantageous. Priority will be given to candidates with the overall highest experience in these fields, however prior experience with all
-
, the student will apply machine learning methods for classification of lung cancer subtype based on the generated MS-data. Finally, the student will evaluate the applicability and value of the developed clinical