Assistant Research Scientist (Molecular Epidemiology lab)
The NYU Bluestone Center for Clinical Research Molecular Epidemiology Laboratory is searching for an outstanding Assistant Research Scientist (Computational Biologist), 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 Assistant Research Scientist (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 incumbent enables the rapid, incremental analysis required to best process and interpret the large amount of data generated in a molecular epidemiology laboratory.
The incumbent 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 incumbent 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.
JOB SPECIFIC TASKS
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).
EDUCATION AND REQUIRED SKILLS EXPERIENCE
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
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
PHYSICAL REQUIREMENTS AND ENVIRONMENTAL CONDITIONS
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
Applicants should submit: 1) Cover letter; 2) Curriculum Vitae; and 3) Names and contact information of at least two professional references. To access the application, please click the "Apply Now" button located on the right.
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