We are currently soliciting applications for computational postdoctoral fellows to undertake exciting projects in computational biology/bioinformatics jointly supervised by Dr. Titus Brown (http://ivory.idyll.org/lab/) and Dr. Fereydoun Hormozdiari (http://www.hormozdiarilab.org/) at UC-Davis.
The successful candidate will undertake computational method and tool development for better understanding the contribution of genetic variation (especially structural variation) on changing the genome structure. In collaboration with the members of both labs, the postdoctoral candidate will also be building models for predicting the changes in gene expression based on variants (especially CNV) and performing a comparative study of genome structures in multiple tissues/samples using Hi-C data.
This opportunity requires developing novel computational algorithms and machine learning methods to solve emerging biological problems. The technical expertise needed include strong computational background to develop novel combinatorial, machine learning (ML) or statistical inference algorithms, with strong programming capabilities and a general understanding of the concepts in genomics and genetics.
Candidates are guaranteed funding for two years and will be strongly encouraged to apply for external funding in the second year of their postdoc to make a successful transition to independent investigator.
Some of the projects to work on include but are not limited to:
- Computational methods to discover and predict the structural variations (SV) which will result in significant modification of genome structure. It is been shown recently that structural variation which results in modification of TAD (Topologically Associating Domains) can result in genetic diseases. As part of this project we are trying to develop methods which would predict which SVs will result in such a significant modification and potentially build a method for ranking/scoring SVs based on their pathogenicity in disease such as autism and cancer.
- Study the effect of SV/CNVs which result in significant changes of genome structure during (great ape) evolution and associated with changes in gene expression for each of these species as a result of such variants.
Develop computational tools for finding conserved and significantly differentiated TADs in two more samples (from different cell types or species) using HiC data, with application to data from different tissues and/or species..
Suggested candidate background:
- Ph.D. in computer science, computational biology or related fields
- Excellent programming skills in at least one language (C/C++, Java or Python)
- Strong written/oral presentation skills
- Enthusiasm for genomics-related problems
- Knowledge of next-generation sequencing technologies and HiC data is a plus.
Interested candidates should send their CV and a research statement to Fereydoun Hormozdiari (email: fhormozd[at]ucdavis.edu) and Titus Brown (email: ctbrown[at]ucdavis.edu).