Assistant Research Scientist - (P.I.: Dr. Bradley Aouizerat)

Description

LABORATORY OVERVIEW

Dr. Aouizerat's laboratory focuses on the identification of molecular mechanisms that underlie symptoms (e.g., pain, fatigue), the impact of substance use (e.g., cannabis use) on disease pathology, sequelae (e.g., neuropathy) and treatment (i.e., pharmacogenomics, pharmacodynamics) of common chronic diseases (e.g., cancer, HIV, nonalcoholic fatty liver disease, cardiovascular disease). Research conducted by the group includes a combination of dry (e.g., bioinformatics) and wet (e.g., molecular biology) approaches. Research topics include development of epigenomic risk profiles, leveraging publically available datasets to complement de novo cohorts, translational research (i.e., study of targets in humans and mice), genomics (i.e., array-based and sequencing-based), transcriptomics (i.e., array-based and sequencing-based), and functional analyses (e.g., wet bench experiments). The Aouizerat Laboratory works closely with other laboratories with expertise in animal and cell models to permit accelerated translation of processes of interest identified in human data.

POSITION OVERVIEW

The Computational Biologist will analyze and manipulate data generated from both internal and external sources, use, modify, or create pipelines and reporting software, and aid other scientists in the group with a variety of computational tasks. By applying a variety of software and technologies, the Computational Biologist enables the rapid, incremental analysis required to best process and interpret the large amount of data generated in a molecular epidemiology laboratory.

 JOB SPECIFIC TASKS

• Develop analytical pipelines for manipulating genomics datasets and interpret results appropriately to ensure accuracy and reliability of those pipelines.
• Collaborate with others in the research team, including statisticians, molecular biologists, molecular epidemiologists, genomic analysts, and other computational biologists to design studies and implement computational applications.
• Assist Dr. Aouizerat with design and conduct of research projects.
• Acquire, update and analyze data from internal (e.g., Aouizerat or affiliated laboratories, Genomic Core Facilities) or external (e.g., TCGA, UCSC Genome Browser, 1000Genomes, dbGaP) sources, document system changes, write and maintain documentation for end users. Prepare and contribute to research papers.
• Determine optimal storage environments; advise and collaborate with IT infrastructure colleagues in implementing, tuning and monitoring systems supporting scientific activities.
• Other duties as assigned. 

In compliance with NYC’s Pay Transparency Act, the annual base salary range for this position is $50,00.00- $60,000.00.  New York University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer.

Qualifications

EDUCATION AND REQUIRED SKILLS EXPERIENCE

Education and Experience:

• Bachelor’s degree in biology, chemistry or other life sciences
• Master’s in Bioinformatics or Computational Biology required, PhD preferred
• Training in biostatistics (e.g., Minor, Master’s Degree) preferred
• Experience with multiple programming languages and computational environments, including UNIX-style operating systems, command line interfaces, R, perl/python or similar, and SQL or other database software.
• Knowledge of current bioinformatics approaches and databases
• Background in statistics and quantitative data analysis, as demonstrated through previous work or academic experience.
• Experience with and knowledge of biological sciences, especially genetics and molecular biology.
• Experience with project management preferred.

Required Skills:

• Excellent programming skills and ability to manipulate large data sets and proficient with design and use of modern relational/non-relational databases.
• Familiarity with most basic system administration tools and processes. Experience administering CentOS/RedHat Linux (FreeBSD desired). Competence in programming in HTML, BASH, SQL, Python/Perl, and other relevant tools; experience with cluster computing.
• Perform basic and advanced analysis on data produced from next generation sequencing systems (e.g., DNA-seq, RNA-seq, metagenomics) as well as genotyping, gene expression, and DNA methylation microarrays.
• Experience with relevant bioinformatic analysis tools/best practices.
• Develop, improve, modify, and operate data analysis pipelines.
• Use or implement current open source software in conducting data analysis