Assistant Research Scientist (Molecular Epidemiology lab)

New York City, New York (US)
August 14 2020
Life Sciences
Organization Type

Assistant Research Scientists (Molecular Epidemiology lab)

The NYU Bluestone Center for Clinical Research Molecular Epidemiology Laboratory is searching for an outstanding Computational Biologist to begin July 1st, 2020, with a strong interest in developing and applying bioinformatic/quantitative methods to problems in the molecular epidemiology of chronic disease risk, treatment, and sequelae.

The Molecular Epidemiology Laboratory, led by Dr. Bradley Aouizerat, is a group of experimental and computational scientists dedicated to understanding the risk factors for and the mechanisms that underlie chronic disease (primarily HIV and cancer), their treatment (i.e., HIV antiretroviral therapy), and its sequelae (i.e., pain, fatigue, neuropathy). Research approaches employed by the group includes a combination of dry (e.g., bioinformatics) and wet (e.g., molecular biology) approaches. The 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. Commonly applied approaches relevant to the current position include:

  • Leveraging publicly available molecular data (i.e., GWAS, transcriptomic, epigenomic, proteomic)
  • Generating molecular data from cohort studies
  • Applying and developing novel multi-omic analysis
  • Identifying therapeutic targets.
  • Optimization of DNA and RNA capture techniques
  • Single-cell genomics applications


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.

The Computational Biologist will communicate bioinformatics analysis to students, postdoctoral trainees, research scientists and investigators, ensure the validity and reliability of data and methods at all times, and maintain accurate and complete records of all analysis projects. The Computational Biologist will identify and develop suitable techniques for the analysis and visualization of data, and build and maintain the associated computational resources (i.e. software packages, databases, or web-based analysis and visualization tools), and will maintain all code and programs used for analysis and tool development with suitable source control.

Other research duties will include authoring and co-authoring several manuscripts per year, assisting with grant writing, collaborating with other investigators, and attending professional conferences. 


  • Assist Dr. Aouizerat with design and conduct of research projects.
  • Apply, modify, or develop analytical pipelines for manipulating genomic datasets and interpret results appropriately to ensure accuracy and reliability of those pipelines. Examples of data routinely analyzed include array-based (i.e., SNP, gene expression, DNA methylation), RNA sequencing (bulk and single cell), DNA sequencing, and methylation capture sequencing.
  • Acquire, update and analyze data from internal (e.g., Aouizerat or affiliated laboratories, Core Facilities) or external (e.g., TCGA, UCSC Genome Browser, 1000Genomes, dbGaP) sources, document system changes, write and maintain documentation for end users.
  • Collaborate with others in the research team, including statisticians, clinicians, molecular biologists, molecular epidemiologists, and computational biologists to design studies and implement computational applications.
  • Prepare and contribute to dissemination of research findings (i.e., manuscripts, lab meeting presentations, presentations at scientific meetings).




  • Required
  • Bachelors degree in biology, chemistry or other life sciences
  • Ph.D. in Bioinformatics, Statistics, Mathematics, Physics, Computer Sciences or related discipline
  • Excellent programming skills with multiple programming languages and computational environments, including UNIX-style operating systems (e.g., Linux), command line interfaces, R, perl/python, BASH, Matlab, or similar, and SQL or other database software
  • Knowledge of current bioinformatics approaches, databases, and best practices
  • Able to work both independently and collaboratively
  • Be highly motivated, have excellent analytical, problem-solving, and time management skills
  • Excellent oral and written English communication skills
  • Outstanding interpersonal and teamwork skills
  • Excellent analytical, problem-solving, organizational and time management skills
  • Preferred
  • Background in statistics and quantitative data analysis, as demonstrated through previous work or academic experience. Training in biostatistics (e.g., Minor, Master’s Degree)
  • Experience in use of machine learning approaches
  • Experience with and knowledge of biological sciences, especially genetics and molecular biology
  • Experience with project management preferred
  • At least 1 year of demonstrated exposure to NGS data analysis; experience using standard nextgen sequencing analysis software (including samtools, GATK, Picard, bedtools)
  • Experience working with TCGA, COSMIC, 1000 Genomes, ENCODE, or GTEx data
  • Programming skills in C++ or Java a plus
  • 2-4 prior post-doctoral experience


The physical requirements and environmental conditions of this position consist primarily of:

  • Continuous mental and visual attention, requiring sustained attention and observation
  • Ability to work at a PC monitor for most of the work day

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