Postdoctoral Fellowship position - Data Driven Machine Learning

The lab of professor Jesper Tegnér at KAUST has openings for three postdoctoral fellowships in Data-driven Machine Learning for unbiased Discovery of Generative Models with special reference to Single Cell Analytics.

The Living Systems Laboratory (livingsystems.kaust.edu.sa) offers an excellent interdisciplinary environment where experimentalists work closely with computational experts utilizing state-of-the-art genomic technologies. We ask fundamental questions on how cells operate as molecular machines with special reference to the dynamic gene regulatory networks governing cellular identity and stability of states. We believe that adaptive molecular circuits in living systems hold secrets to new properties beyond what is readily apparent from the fundamental equations of matter. In our quest of discovering principles of natural adaptive computation and fundamental understanding of cells – the building blocks of life we use a blend of computational, experimental, and theory-driven approaches.

We are now recruiting 3 postdoctoral researchers (https://postdoc.kaust.edu.sa/Pages/Home.aspx ) with a strong computational and/or theory background to develop novel computational methods. We are in particular targeting development of data-driven high-performance computing techniques for unbiased discovery of generative models & theory and algorithms for network inference with special reference to multi-omics single cell data. The 3 positions require skills (each in different degrees and balance) on high-performance computing, dynamical systems, machine learning techniques for high-dimensionality data-analysis, information theory, unsupervised learning and artificial intelligence, programming, appropriate numerical schemes and efficient implementation of algorithms. Positions include (i) theory and algorithms for efficient learning of dynamical models of micro-states evolving over time including machine based learning of derivation of coarse grained representations; (ii) implementation of large-scale computational schemes involving learning algorithms and dynamical systems models; (iii) application and fine-tuning of these tools using single cell data from stem cells, immune cells, and neurons.                                                                    

We are embedded in BESE division (bese.kaust.edu.sa), which extends and supports a multi-disciplinary work environment. Furthermore, through the core laboratories

(corelabs.kaust.edu.sa) such high-performance computing, extreme computing, visualization, and the bioscience core. Our workplace is truly international. We have several international collaborations, including Karolinska Institutet (compmed.se). Due to the number of ongoing collaborations with teams in Europe and US and the successful candidates are expected to interact and travel with those teams depending on the specific project needs.          

About KAUST

King Abdullah University of Science and Technology (KAUST ) is being established in Saudi Arabia, on the Red Sea coastal area of Thuwal, as an international graduate-level research university dedicated to inspiring a new age of scientific achievement that will benefit the region and the world. As an independent and merit-based institution and one of the best-endowed universities in the world, KAUST intends to become a major new contributor to the global network of collaborative research. It will enable researchers from around the globe to work together to solve challenging scientific and technological problems. The admission of students, the appointment, promotion and retention of faculty and staff and all the educational, administrative and other activities of the University shall be conducted on the basis of equality, without regard to race, color, religion or gender. The leading position of KAUST with respect to research output in the region and the world was recognized by the QS World University Rankings 2016-2017 , which ranked the University first globally in the category of Faculty Citations.Further information can be found at www.kaust.edu.sa .