Assistant / Associate / Full Professor in Bioinformatics and Systems Biology
6 days left
- Full Time
King Abdullah University of Science and Technology:
Faculty Positions: Biological and Environmental Science and Engineering Division (faculty)
King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
King Abdullah University of Science and Technology (KAUST) has launched a Smart Health Initiative (SHI) with the goal of establishing a world class research capability to tackle various technological and scientific challenges related to Precision Medicine and its implementation in clinical practice. KAUST-SHI aims to build engineered models of human diseases, network biology, functional genomics capitalizing on new emerging genome-wide techniques and advances in computational approaches in molecular medicine (Bioinformatics) as well as biomedical use of Artificial Intelligence (AI) and Machine Learning (ML). To fulfil these goals, KAUST-SHI, in collaboration with the Divisions of Biological and Environmental Science and Engineering (BESE) and Computer, Electrical and Mathematical Science & Engineering (CEMSE), is inviting applications from highly qualified candidates to fill positions at Assistant, Associate and Full Professor levels. While high level candidates in the general field of Bioinformatics, AI and Ml and their application to health are encouraged to apply, an emphasis will be made on the following areas:
- Translational Bioinformatics and Systems Medicine: We are seeking candidates who have expertise in relevant multi-omic data sets, integrative systems analysis with special reference to biomedical data sets and to develop and apply techniques enabling data integration and systems analysis, contributing to Precision Medicine.
- Machine Learning and Artificial Intelligence for Deep Genomics Analysis for Biology: We are seeking candidates who can develop methods and applications such as Deep Convolutional Networks, Generative Adversarial Networks and Bioinformatics with specialization in Genomics. Expertise on application areas in Biology including cell and molecular biology to facilitate translation to personalized medicine practice will be desirable. Candidates with such expertise may be encouraged to collaborate in programs on food and nutrition genomics, plant genomics, and marine genomics at KAUST.
- Machine Learning for Medicine and Biology: We are seeking candidates who will develop methods in subareas of ML and AI and applications such as Natural Language Processing, Medical Image Analysis and Health Care data Analysis. Focusing on relevant areas such as processing of medical records, analysis of medical images derived from pathologies such as tumors and cellular imaging technologies will be of special interest. In addition, expertise in the fields of Deep Convolutional Networks, Graph embeddings, Text Mining and Adversarial Techniques will be highly desirable.
Basic qualifications for the positions at all levels are PhD and 2-3 years of postdoctoral training in relevant fields/subareas. Candidates applying for Assistant Professor Positions should demonstrate an excellent potential for conducting high impact research and developing a teaching program. Those applying for Associate or Full Professor positions should have a distinguished track record of research and publications in top-tier venues of their respective areas, and a strong commitment to services, mentoring and teaching at graduate level as well as fostering interdisciplinary collaborative research at KAUST.
The positions will remain open until filled. The applications will be rigorously reviewed by the Search Committee consisting of experts in the relevant fields, and only applicants who are short listed will be contacted for further consideration.
KAUST (httpps://www.kaust.edu.sa/en) located in the beautiful 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 and economic and health challenges through its highly funded bold and collaborative research of regional and global significance. The KAUST-SHI recruited faculty may be cross appointed at the Division of Biological and Environmental Science and Engineering (BESE); see https//bese.kaust.edu.sa. Information about KAUST SHI can be found at https://smarthealth.kaust.edu.sa. KAUST offers a unique combination of an intellectually stimulating environment and an access to world-class laboratories, instrumentation, and a generous funding scheme. The facilities include state of the art core facilities in Genomics, Proteomics, Imaging and Characterization,Extreme Computing and Informatics, and animal facility. The positions come with an internationally (highly) competitive salary, attractive benefits, and start-up packages for top-notch applicants. Applicants at all ranks will be considered to recruit excellent candidates without demographic or gender preference. Female candidates and junior researchers are particularly encouraged to apply. The positions may remain open until filled or declared as closed. The applications will be rigorously reviewed by the Search Committee consisting of experts in the relevant fields, and only applicants who are short listed will be contacted for further consideration.
To prevent any delays in reviewing your application, you will need to upload the following materials:
- A cover letter introducing your candidacy and explicitly stating both the position and the rank. The rank must be consistent with the candidate’s experience.
- Up-to-date Curriculum Vitae including full publication list.
- Statement of research interests (5 pages maximum).
- Statement of teaching interests (2 pages maximum) including teaching philosophy and an outline of 1-2 graduate planned graduate teaching course(s).
- Names and contact information for at least 4 references. Referees should have positions in academic or industrial research laboratories. In the case of Associate and Full Professor applications, the referees should be of a rank higher or equivalent to that of the candidate.
- Copies of most relevant publications (Maximum of five).