Postdoctoral Fellowships, 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 (http://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 (http://bese.kaust.edu.sa), which extends and supports a multi-disciplinary work environment. Furthermore, through the core laboratories (http://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 (http://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.

The candidates are expected to have a strong motivation to identify and solve scientific problems in an interdisciplinary collaborative research environment. The postdoc will work in close collaboration with, computer scientists, bioinformaticians, and molecular biologists but is expected to run his/her own project independently. A strong track record from computational projects, a passion for science and good interpersonal skills are prerequisites for the position.

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