Postdoctoral Fellow - Livestock Population Genomics

Job Description

The position is available—initially for one year—from XXX, 2025, or as soon as possible thereafter—with the possibility of extension for four years. The Khalifa Centre for Genetic Engineering and Biotechnology employs cutting-edge population genomics, animal science technologies and bioinformatics to decipher the mechanisms of local adaptation and production traits in mammals. In this project, the successful candidate will develop new computational strategies to identify the structure of UAE camel, cattle and sheep breeds and candidate genetic variants for improved breeding strategies. The candidate will utilise and combine Illumina DNA SNP array genotyping and whole-genome sequencing, long-read sequencing, and RNA sequencing. The candidate can explore new analysis methods using high-performance computer clusters. Depending on their interest, it is possible to be involved in wet lab experiments and perform DNA and RNA extraction.

Minimum Qualification

• PhD in Bioinformatics, Computer Science, Physics, Engineering, Bio-engineering, or equivalent
• Excellent track record in Bioinformatics with at least one first-author publication, accepted or submitted
• Experience with machine learning will be a plus (e.g., Tensorflow/Keras/PyTorch).
• Programming experience is required (Python, R).
• Previous experience in genomics population data analysis
• Strong analytical, organizational, and record-keeping skills
• Interest in working in a multidisciplinary and multicultural team
• Willing to collaborate with internal and external collaborators, travel internationally, as well as support group members
• Experience and interest in supervision
  
  

• PhD in Bioinformatics, Computer Science, Physics, Engineering, Bio-engineering, or equivalent
• Excellent track record in Bioinformatics with at least one first-author publication, accepted or submitted
• Experience with machine learning will be a plus (e.g., Tensorflow/Keras/PyTorch).
• Programming experience is required (Python, R).
• Previous experience in genomics population data analysis
• Strong analytical, organizational, and record-keeping skills
• Interest in working in a multidisciplinary and multicultural team
• Willing to collaborate with internal and external collaborators, travel internationally, as well as support group members
• Experience and interest in supervision
  
  

• Employ computational strategies to identify the genetic structure of local domestic animals
• Analyze bulk, whole-genome sequencing datasets using HPC
• Contribute to projects on whole-genome association studies to find links between variation and genotype
• Support research and development activities within the group
• Maintain accurate and detailed records of research activities
• Support the project leader in everyday routines, including training new group members
• Collaborate with an external partner
• Engage in teaching and supervision as required