An opening for a PhD, or MSc+PhD, student position is available in the group of Robert Hoehndorf at the King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
Group website: http://borg.kaust.edu.sa
Research area: Machine learning and ontologies in biology
Location: Thuwal, Saudi Arabia
Application deadline: Fall 2017
Some recent advances in machine learning have led to feature learning methods that can learn the regularities (i.e., the "conceptualization") underlying a domain. Ontologies are the explicit, symbolic representations of these conceptualizations. There still remains a gap in AI between the distributed representations that are learned by recent machine learning algorithms and the symbolic representations of the same phenomena. Closing this gap is a major remaining challenge for AI with significant impact in biology and biomedicine in which a large number of symbolic representations (ontologies and knowledge graphs) have been developed and are applied. In this project, the PhD student will work on the boundaries between statistical and symbolic approaches to AI and develop novel AI methods with applications in biology and biomedicine. Major application areas include understanding molecular mechanisms underlying traits, phenotypes, and disease, and identifying ways to perturb biological systems through bioactive compounds (drugs).
The student will join a productive research team at one of the fastest-growing research universities, located in Thuwal, KSA, by the Red Sea.
Expertise required: - MSc degree (of BSc degree for MS+PhD applicants) at the Commendation/Distinction level in computer science, electrical engineering, or mathematics. - Excellent programming skills. - Experience in machine learning, optimization, knowledge representation, Semantic Web technologies, or bioinformatics is desirable but not required.
Students are entitled to a competitive stipend, free, fully-furnished housing on the KAUST campus, free medical and life insurance, and free education at KAUST schools for the student's children. KAUST will be responsible for the actual admission offer, stipend and benefits.
How to apply:
Full application must be submitted through the application website at https://www.kaust.edu.sa/en/study/applying-to-kaust. Before applying, please send your CV and a brief letter of motivation by email to email@example.com.
For any questions related to the position, please contact firstname.lastname@example.org.