Research Assistant Professor

Job Description
The Khalifa Center for Genetic Engineering and Biotechnology invites applications for a faculty position specializing in Epigenetics and Non-Coding RNAs. The successful candidate will lead cutting-edge research into the regulation of gene expression through epigenetic mechanisms and non-coding RNAs, with applications in agriculture and environmental adaptation. This role supports the Center's vision for advancing food security and sustainable development.
Key Responsibilities:

1. Research:
   Conduct innovative research on the role of epigenetic modifications (e.g., DNA methylation, histone modifications) and non-coding RNAs (e.g., lncRNAs, siRNAs, miRNAs) in biological processes.
2. Focus on applications such as:
   
   1. Abiotic stress tolerance in plants.
   2. Epigenetic therapies for diseases.
   3. Non-coding RNA roles in adaptation and evolution.
3. Publish high-quality research in top-tier journals.
4. Secure external research funding and develop collaborative projects.
5. Service:
   Contribute to Center's committees. Foster interdisciplinary collaboration with other departments and research centers. Engage in outreach programs to promote awareness of epigenetics and its applications.

Minimum Qualification:
Ph.D. in Molecular Biology, Genetics, or a related field with a focus on epigenetics or non-coding RNAs.
Strong track record of research excellence, including publications in peer-reviewed journals.
Experience with cutting-edge epigenomic technologies such as:

1. Chromatin immunoprecipitation (ChIP).
2. RNA sequencing and small RNA profiling.
3. DNA methylation analysis.

Preferred Qualification:
Experience in applying epigenetics and non-coding RNAs to real-world challenges, such as:

1. Crop improvement and food security.
2. Environmental adaptation and stress response.

Proven ability to secure research funding.
Prior teaching experience at the university level.
Expected Skills:
Expertise in bioinformatics and computational tools for analyzing epigenomic and transcriptomic data.
Strong organizational and leadership skills for managing research teams.
Ability to work collaboratively across disciplines.
Effective communication and mentoring skills for diverse student and faculty populations.