Post Doctoral Fellow

About Khalifa University and the UAE: Khalifa University is a leading research-intensive institution located in Abu Dhabi, UAE. As an emerging international hub for research and innovation, the UAE offers a dynamic, multicultural environment, particularly strong in areas such as AI, genomics, and precision medicine. Khalifa University has state-of-the-art facilities and resources and ranked 177th globally in the QS World University Rankings.

• We are seeking a highly motivated and independent postdoctoral fellow to join a multidisciplinary research project investigating the molecular mechanisms underlying obesity therapy outcomes using multi-omics data integration and machine learning approaches.
• The successful candidate will contribute to cutting-edge research involving genome sequencing, DNA methylation profiling, metagenomic analysis, and other omics.
• The position offers an exciting opportunity to work in an internationally competitive environment and contribute to the development of predictive models with potential clinical applications.
• Drive innovative research in multi-omics data analysis, contributing to groundbreaking advancements in obesity therapy and personalized medicine.

The post-doctoral fellow will be responsible for the following activities:

• Perform comprehensive analyses of genome sequencing, DNA methylation, and metagenomic datasets.
• Develop and apply integrative bioinformatics pipelines for multi-omics data analysis.
• Contribute to the development of machine learning models for predicting therapy outcomes.
• Collaborate with team members to interpret results and publish high-impact scientific papers.
• Mentor and support PhD and undergraduate students in bioinformatics-related analyses.
• Assist in preparing project reports, manuscripts, and grant proposals.
• Present findings at national and international scientific meetings.
• Maintain documentation of data processing, pipeline development, and analyses.
• Participate in internal and external collaborations across departments and institutions.
• Contribute to teaching and training activities as assigned.
• Provide technical supervision and mentorship to PhD students and junior researchers in omics data analysis.
• Guide student researchers on best practices in bioinformatics and reproducible research.
• Participate in the academic and professional development of junior team members.
  Experience in analyzing large-scale biological datasets, proficiency in programming languages such as Python or R, and knowledge of statistical methods are essential. Familiarity with tools like BLAST, Bowtie, and Galaxy is a plus. Prior experience in publishing in peer-reviewed journals is highly valued.