The post-doc will develop and implement computational algorithms and a system to study computationally derived gene regulatory networks, in conjunction with existing public database of signaling pathways such as Pathway Commons. The post-doc will also assist in developing grant proposals, based on the outcomes of aforementioned research, in addition to publishing research results.
In addition, the post-doc will co-mentor students (high school, undergraduate and/or graduate students) in related research.
Translational Genomics Research Institute (TGen)
The Seungchan Kim lab (Biocomputing Lab) at TGen focuses on development and application of computational methods to analyze high throughput genomic and transcriptomic data.
Our research incorporates statistical and computational tools to study cancer biology, focusing on:
identification of biomarkers and/or therapeutic targets for cancers,
molecular classification of cancers, and
understanding and mathematical modeling of genetic regulatory networks, with the special focus on contextual genomic regulation.
Detailed Description
Develop a system to archive computationally derived gene regulatory networks (cGRNs) from public data such as TCGA and ICGC.
Develop algorithms to analyze archived cGRNs.
Develop algorithms to identify condition-specific GRN.
Mentor students (high school, undergraduate and/or graduate students) in related research
Collaborate with other scientists within and outside the institute.
Job Requirements
Ph.D. in bioinformatics, computational biology, or computer science with experience related field of research.
Strong programming skills C/C++ or Java.
Experience with public genomic database such as TCGA is required.
Experience in database system, especially noSQL, is desired.
Read more/Apply online:
The post-doc will develop and implement computational algorithms and a system to study computationally derived gene regulatory networks, in conjunction with existing public database of signaling pathways such as Pathway Commons.
