Job ID: 687273
Job date: 2019-05-16
End Date: 2019-07-08
Company : USC Leonard Davis School of Gerontology Country : United States Role : Postdoc
Job date: 2019-05-16
End Date: 2019-07-08
Company : USC Leonard Davis School of Gerontology Country : United States Role : Postdoc
Job Description:
The Benayoun laboratory (http://gero.usc.edu/labs/benayounlab/) at the USC Leonard Davis School of Gerontology focuses on the study of how aging influences gene regulation, and in return, how modulation of the epigenome and transcriptome can influence the aging process. To study this question, we use a unique combination of high-throughput ‘omics’ approaches, machine-learning, and experimental validation in vertebrate aging models (e.g. mouse, African turquoise killifish, etc.). The goal of the lab is to discover novel target genes and pathways playing a fundamental role in healthy and pathological aging, while leveraging the power of big data to directing experimental interventions.
The laboratory is seeking a skilled and motivated computational scientist to join the lab as a postdoctoral fellow and make leading contributions to aging research. This is a unique opportunity for a computational scientist to work closely with experimental biologists, analyze cutting-edge data types (e.g. ATAC-seq, RNA-seq, single cell data), and help develop new analytical frameworks for data integration.
Additional Info:
Successful candidates should have strong training and publication records, and must be able to learn and work independently, yet collaborate effectively with co-workers within the lab and with collaborators. The ideal candidate will have training in biostatistics, computational biology or computer science. Programming skills in a statistical language (e.g. R) and/or a scripting language (e.g. Perl, Python) are required, and knowledge of genomics, machine-learning, and UNIX-based environments are desired. Candidates should have, or will soon receive, a Ph.D. or equivalent diploma in computational biology, genetics, or a relevant subject area. The successful candidate will work closely with the PI. Extensive training will be available in all areas of highly impactful projects, with a strong view towards enhancing future career prospects of the successful candidate. [Click Here to Access the Original Job Post]
The Benayoun laboratory (http://gero.usc.edu/labs/benayounlab/) at the USC Leonard Davis School of Gerontology focuses on the study of how aging influences gene regulation, and in return, how modulation of the epigenome and transcriptome can influence the aging process. To study this question, we use a unique combination of high-throughput ‘omics’ approaches, machine-learning, and experimental validation in vertebrate aging models (e.g. mouse, African turquoise killifish, etc.). The goal of the lab is to discover novel target genes and pathways playing a fundamental role in healthy and pathological aging, while leveraging the power of big data to directing experimental interventions.
The laboratory is seeking a skilled and motivated computational scientist to join the lab as a postdoctoral fellow and make leading contributions to aging research. This is a unique opportunity for a computational scientist to work closely with experimental biologists, analyze cutting-edge data types (e.g. ATAC-seq, RNA-seq, single cell data), and help develop new analytical frameworks for data integration.
Requeriments :
Skills :
- Bioinformatics
- Biomedical Research
- Biostatistics
- Computational Biology
- Genomics
- Linux/Unix
- Machine Learning
- Programing in Python
- Programming in PERL
- Programming in R
- Shell scripting
- Strong Communication Skills
- Strong publication record
Areas :
Additional Info:
Successful candidates should have strong training and publication records, and must be able to learn and work independently, yet collaborate effectively with co-workers within the lab and with collaborators. The ideal candidate will have training in biostatistics, computational biology or computer science. Programming skills in a statistical language (e.g. R) and/or a scripting language (e.g. Perl, Python) are required, and knowledge of genomics, machine-learning, and UNIX-based environments are desired. Candidates should have, or will soon receive, a Ph.D. or equivalent diploma in computational biology, genetics, or a relevant subject area. The successful candidate will work closely with the PI. Extensive training will be available in all areas of highly impactful projects, with a strong view towards enhancing future career prospects of the successful candidate. [Click Here to Access the Original Job Post]