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
A doctorate in a relevant discipline area, such as Computer Science, Physics, Computational Mathematics. 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
undefined page loaded Already have an account? Sign In Postdoctoral Fellowship position - Data Driven Machine Learning King Abdullah University of Science and Technology: Postdoc Positions: Biological and Environmental Science and Engineering Division Location Thuwal, Saudi Arabia Open Date Jul 11, 2018 Description 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. Qualifications 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. Requirements Creative and self-motivated personality with interest in fundamental and applied science Excellent problem-solving skills Good interpersonal skills Excellent communication skills in English High-level written and oral communication skills with the ability to represent the research team at national and international conferences. A record of publications in quality, peer reviewed journals A doctorate in a relevant discipline area, such as Computer Science, Physics, Computational Mathematics. Application Instructions Application should include Single Page Cover letter including a description of your research experience and your research interests CV including list of publications Copy of official academic transcripts Three letters of reference Other information The starting date is flexible. Please indicate approximate starting date. For further details about the position, please contact Prof. Jesper Tegnér (firstname.lastname@example.org) institution logo Application Process This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge. Apply Now Powered by Interfolio Opens in new window
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