Open Positions at Bluestone


At Bluestone Center for Clinical Research, we are currently offering the following positions:

Laboratory Technician (Cancer Pain Lab) (full-time)

The NYU Cancer Pain Laboratory has recruited, trained, and promoted a handful of gifted investigators to investigate neuronal mechanisms of cancer pain.   Much of our research utilizes preclinical models of oral cancer, most notably, squamous cell carcinoma. Our researchers pursue studies on the interaction between squamous cell carcinoma and peripheral afferent fibers in the cancer microenvironment.  In cell based research as well as studies that employ patient specimens we seek to leverage scientific discovery for improved patient care.  

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Assistant Research Scientist (Computational Biologist) (full-time)

Dr. Aouizerat's laboratory focuses on the identification of molecular mechanisms that underlie symptoms (e.g., pain, fatigue), sequelae (e.g., lymphedema, 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 another laboratory 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.

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