Join our team
GENERAL SUMMARY OF POSITION:
We are seeking a highly motivated, creative and independent individual to join our program to create algorithms to create accurate gene and isoform annotations in a collaboration between the UMMS Bioinformatics Core (https://www.umassmed.edu/biocore) and Garber laboratory (Computational Biology, http://garberlab.umassmed.edu). We are pursuing a modeling, data centric, approach that integrates multiple RNA-Seq libraries. This is a unique opportunity for building, testing and refining computational models to create more accurate gene/isoform annotations.
The person hired for this position will lead the data handling, analysis and algorithm development efforts. As such the ideal candidate will be intimately familiar with machine learning, classification and clustering algorithms, sequencing technologies and have a working knowledge of computational biology.
Key responsibilities include:
● Responsible for analysis of bulk RNA-Seq data
● Statistical modeling of genomics data
● Development of computational tools for de-novo transcriptome assembly using RNA-Seq data
● Develop, validate, and compare the performance of prediction models.
● Use demonstrated scientific creativity, collaboration with others, and independent thought to expand technical capabilities and identify new research opportunities
● Ph.D or masters degree in Bioinformatics, Computational Biology, Physics, Computer Science, Statistics or related field
● Working knowledge of computational biology and sequencing technologies
● Fluency in at least one scripting language (e.g. Python, Perl) and good knowledge of non-scripting languages (e.g. C++)
● ANSI sql and nosql knowledge to fast and scalable databases
● Strong publication record and excellent communication skills
● Excellent organization and time management skills
● Must be able to handle a variety of tasks and to adapt to a highly dynamic environment
To apply, please forward CV, statement of research and contact information for three references to:
Alper Kucukural, PhD
Assistant Professor, Molecular Medicine
University of Massachusetts Medical School
368 Plantation Street, AS6-2061
Worcester, MA 01605