Assistant/Associate/Full Professor in Machine Learning & AI for Deep Genomics Analysis for Biology
King Abdullah University of Science and Technology: Faculty Positions: Biological and Environmental Science and Engineering Division (faculty)
King Abdullah University of Science and Technology
The Biological and Environmental Science and Engineering Division (BESE) at King Abdullah University of Science & Technology (KAUST) is accepting applications for several faculty positions (Open Rank: Assistant, Associate or Full Professor) in the broad area of Machine Learning, Artificial Intelligence for Deep Genomics Analysis across all areas of Biology. Candidates applying for a position of Assistant Professor should have an excellent potential for high impact research. Candidates applying for Associate and Full Professor positions should have a distinguished track record in research and a strong commitment to service, mentoring, teaching at the graduate level and making an impact in interdisciplinary research. Applications at any rank and of any demographic will be considered, although female candidates and junior researchers are particularly encouraged to apply.
KAUST is seeking candidates with an established track record of research in one of the subareas of Machine Learning or Artificial Intelligence, with special reference to method development and applications such as Deep Convolutional Networks, Generative Adversarial Networks and Bioinformatics with specialization in Genomics. Application areas in Biology include cell and molecular biology, food genomics, plant genomics, and marine genomics. Successful candidates will have a PhD in Bioinformatics, Computational Biology, Computer Science, Applied Mathematics, Bioengineering, Statistics, or related fields, as well as a strong publication record in the top-tier venues of their respective areas.
These positions are part of a strategic expansion of KAUST in the areas of Smart Health, Bioengineering, Machine Learning and Artificial Intelligence.
KAUST offers a unique combination of an intellectually stimulating environment, relevant medical and biological research problems, and access to relevant data and world-class facilities, including KAUST’s 5 petaflops Shaheen-2 supercomputer and GPU clusters. KAUST's unique funding and organizational structure allows faculty to prioritize their research program over other professional activities.
Basic Qualifications: PhD with 2-3 years of Postdoctoral training.
Demonstrated commitment to research and teaching is desired. Dependent upon experience, candidates should provide evidence of strong scholarly potential and the interest and capacity to make novel and impactful discoveries in a collaborative setting.
KAUST (https://www.kaust.edu.sa/en), located on the shores of the Red Sea in Thuwal (80km north of Jeddah) in Saudi Arabia, is an international graduate-level research university dedicated to advancing science and technology through bold and collaborative research and to addressing challenges of regional and global significance. For more information about KAUST, please visit http://www.kaust.edu.sa. More information about the Biological and Environmental Science and Engineering Division (BESE) is available at http://bese.kaust.edu.sa/.
The first round of applications will be reviewed beginning March 15, 2020 and positions will remain open until filled.
Please upload the following documents:
- Cover letter
- Curriculum Vitae which includes full publication list
- Research Statement (4 pages maximum)
- Teaching Statement (2 pages maximum) including teaching philosophy and an outline of 1-2 graduate course(s) to be taught
- Diversity Statement (2 pages maximum) describing commitment and strategies to promote diversity and inclusion in a research and teaching environment
- For an Assistant Professor position: the names and contact information for at least 4 references
- For Associate and Full Professor positions: a list of names and contact information for referees who have positions in academic or industrial research laboratories of a rank higher or equivalent to that of the candidate