Research Associate

A global higher education leader in innovative teaching, research and public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation's top public universities. Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn.

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The UNC Eshelman School of Pharmacy (www.pharmacy.unc.edu) is one of six health science schools (Pharmacy, Nursing, Dentistry, Social Work, Public Health, Medicine) at the University of North Carolina at Chapel Hill and is one of the oldest health science academic programs at Chapel Hill. The School teaches approximately 600 PharmD students and 145 graduate students. The School has built a reputation for its continued pursuit of excellence, rigorous education and training programs, cutting-edge multidisciplinary research, progressive pharmacy practices, efficient business operations, and its outstanding faculty, staff, and students. The School was named the number one School of Pharmacy in the U.S. by the U.S. News and World Report. The School has experienced unprecedented growth and success and continues to strategically position itself for sustained impact, as articulated in the School's Strategic Plan (https://pharmacy.unc.edu/about/oe/strategic-plan/).

Our Vision is to be the global leader in pharmacy and pharmaceutical sciences. Our Mission is to prepare leaders and innovators to solve the world's most pressing health care challenges. We are Advancing Medicine for Life through innovation and collaboration in pharmacy practice, education, research, and public service.

The Laboratory for Molecular Modeling ( MML) in the UNC Eshelman School of Pharmacy is a computational research group that developed and employs machine learning, AI, and data science tools to advance drug discovery. We are seeking a Research Associate to support computational methodology, tool development and applications to drug targets. The person hired will join MML and support both development projects and applications studies especially for intrinsically disordered protein targets as primary responsibility. The research associate will function as part of a multidisciplinary team. The hired individual is also expected to take on some lab organization and maintenance responsibilities, including but not limited to maintaining software, databases, and general maintenance and upkeep of laboratory space.

PhD in Medicinal Chemistry or related field (or foreign degree equivalent) with strong evidence of cheminformatics component

PhD in Medicinal Chemistry or related field (or foreign degree equivalent) with strong evidence of cheminformatics component. Relevant post-baccalaureate degree required (or foreign degree equivalent)
* Experience with standard computational chemistry and cheminformatics techniques
* Experience with QSAR modeling methods
* Experience with molecular docking approaches
* Experience with hit to lead optimization tools
* Experience with virtual screening
* Experience working in a research laboratory
* Ability to work as part of a multidisciplinary team
* Expertise in computational medicinal chemistry, and collaborative studies with experimental colleagues
* Familiar with key machine learning approaches including k-Nearest Neighbor, Support Vector Machines, Random Forest, and neural network techniques
* Working knowledge of software packages such as Glide and AutoDock
* Must be able to prepare presentations and manuscripts as well as demonstrate a high level of attention to detail and quality

Experience with manuscript preparation and submission
* Understanding of computational tools supporting the entire drug development workflow
* Familiarity with biological pathways

Not Applicable.

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