Postdoctoral Fellow in Livestock Population Genomics
The position is available—initially for one year—from year 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 and animal science technologies including bioinformatics to decipher the mechanisms of local adaptation and production traits in sheep.The successful candidate will develop new computational strategies to identify the structure of UAE sheep breeds and candidate genetic variants for improved breeding strategies. The candidate will utilize 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.
• 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
You will • Employ computational strategies to identify the genetic structure of local sheep breeds • 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 external partner • Engage in teaching and supervision as required
31/05/2025