The lab of professor Moradigaravand at KAUST has an opening for one postdoctoral fellowship in Bioinformatics (postdoc.kaust.edu.sa), as part of the KAUST Smart Health Initiative, to investigate the genetic basis of key clinical features of bacterial infections. This position suits recent PhDs, MD/PhDs, with a career interest in computational biology, microbial evolution and bioinformatics working in an interdisciplinary team. The position is fully funded (2 years) including salary and generous project funding, with possibility for extension.
The Infectious Disease Epidemiology (IDE) Laboratory 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 bacterial phenotypes are determined by their genotypes in natural settings. We therefore utilize a broad range of high-throughput genomic and phenomic technologies to obtain whole genome sequencing of clinical and environmental bacterial strains and their key clinical phenotypes under various conditions. We then employ computational methods, in particular machine learning methods, to integrate the phenome and genome data with the goal of reconstructing the genotype-phenotype map and identifying robust causative and informative genomic biomarkers. The post-holder will conduct computational analysis of large-scale genomic collections and develop machine learning framework in collaboration with experimentalists and clinicians in the lab. We honestly think that asking deep questions in a team of different mindsets working together is a path towards fundamental understanding as well as enabling biomedical applications.
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) we have access to the most recent equipment such as imaging, sequencing, and single-cell genomics. The IDE lab is part of the Smart Health Initiative (www.smarthealth.kaust.edu.sa), which aims at the development and usage of smart-health technologies and knowledge to promote innovation that transforms healthcare delivery system of Saudi Arabia and the world from traditional medicine to precision medicine. Central to this initiative, is the collaboration between KAUST scientists with clinicians in the best in-Kingdom medical centers.
The ideal candidate combines experience and interest in genomics, molecular evolution and population genetics to address key questions about the evolution of pathogens in clinical settings. The postholder will also contribute to several large-scale nation-wide population genomics and genomic epidemiology projects by preparing samples for omic analyses such as whole genome sequencing and metagenomics. It is a plus if you know or are interested in microbial evolution and computational biology.
You are highly motivated, energetic, determined, well organized, self-motivated, and independent. You have a well-developed ability and the appropriate temperament to work collaboratively within a multidisciplinary team. Here you are open-mined and critical at the same time while ready to speak up. You like to solve scientific problems, and have a strong work ethic, integrity, and professionalism.
The position is initially limited to 2 years but can be extended.
The preferred starting date is in June 2023. Please indicate approximate starting date.
For further details about the position, please contact Prof. Danesh Moradigaravand (firstname.lastname@example.org)
Applications will be reviewed on a rolling basis until the position is filled.
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. Further information can be found at www.kaust.edu.sa.
- Creative and self-motivated personality with interest in fundamental and applied science
- Previous publications as first author in leading journals in the field of computational biology and genomics
- Extensive experience of programming in R, Python and bash scripting
- Prior hands-on experience of handling big genomic data
- Familiarity with statistical and machine learning methods in R or Python
- Familiarity with next generation sequencing technologies
- 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 applied mathematics, computational biology, physics, computer science or any related quantitative field
Application should include
- Single Page Cover letter
- CV including list of publications
- Copy of official academic transcripts
- Names, e-mail addresses, and telephone numbers for three reference persons if not three letters of recommendations are included in the application. Letters in the application are preferred.
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