KING ABDULLAH UNIVERSITY OF SCIENCE & TECHNOLOGY

Assistant/Associate/Full Professor in Machine Learning for Medicine and Biology

2 days left

Location
Thuwal, Saudi Arabia
Posted
25 Sep 2020
End of advertisement period
25 Oct 2020
Contract Type
Permanent
Hours
Full Time

Location King Abdullah University of Science and Technology

Description

Position Description:

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 for Medicine and 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 specifically 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 Natural Language Processing, Medical Image Analysis, and Health Care. Relevant areas include processing of medical records, image analysis of medical images derived from anomalies such as tumors, and cellular imaging technologies. Experience in or several of the areas of Deep Convolutional Networks, graph-embeddings, text-mining, and Adversarial techniques is required. Successful candidates will have a PhD in Computer Science, Engineering, 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, Machine Learning, Bioengineering, 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.

Additional Qualifications:

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.

Application Instructions

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

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