Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
-based methods to improve cancer therapy Your profile Qualifications PhD in bioinformatics, computer science, biology, medicine, or mathematical statistics. Experience in cancer research and analyses
-
) 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
-
different aspects of evolvability – the ability of organisms to evolve. We are interested in developing computational and mathematical tools to understand and quantify evolvability while exploring its
-
research school. 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
-
vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
-
interdisciplinary backgrounds and expertise to foster cutting-edge research with high clinical relevance. Project Description Imaging methods such as magnetic resonance imaging (MRI), computed tomography (CT), and
-
. 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
-
at developing and applying computational tools to understand the evolution of biodiversity (see https://islandevolution.github.io/ ). As a postdoc in this project, you will work with mathematical modelling
-
documented international research experience, a demonstrated potential for creativity and a high degree of excellence in the field, for example in computational biology, mathematical modelling and simulations