Bioinformatician

  • Location

    Philadelphia

  • Sector:

    Life Sciences

  • Salary:

    Negotiable

  • Contact:

    Jessica Charles

  • Contact email:

    Jessica.Charles@volt.eu.com

  • Job ref:

    BBBH2027_1634203701

  • Published:

    over 2 years ago

  • Expiry date:

    2021-12-13

  • Consultant:

    ConsultantDrop

Role: Bioinformatician

An opportunity to join a small start-up based in Pennsylvania who discover and utilises gene regulatory elements for drug development, precision medicine, and biotechnology by looking at the functional DNA element in the non-coding genome. Their platform works by screening drugs at the preclinical stage, mapping the genome-drug relationship, developing a novel therapeutic application of existing drugs, and precise expression of transgenes in gene therapy and in Ag biotech.

They're looking for someone to apply the fundamental principles of biology to drug development and treatment within their interdisciplinary R&D team and build functional genomics-guided predictive models for drug toxicity and efficacy in multiple cellular, pathological or genetic backgrounds.

Responsibilities:
Analyse functional genomics data (e.g., massively parallel reporter assay data, RNA-seq)
Analyse genomic variations from human populations and cancer genomes
Analyse drug-genome interactions
Build functional genomics-guided predictive models of drug effects
Participate in grant writing and preparation of presentations to stakeholders
Participate in journal clubs to stay current with respect to new and relevant technologies/discoveries
Present data and communicate effectively
Work efficiently with external partners
Work alongside senior leaders to deliver set milestones of the company


Requirements:
Ph.D. in Bioinformatics or related fields
Experience with public genome databases (e.g., TCGA, 1000 Genome, HapMap)
Proficiency in open-source software for population genomics analyses
Proficiency in NGS analysis
Proficiency in statistical analysis
Proficiency with R and Python/Perl
Experience in Machine Learning techniques