Research Associate

The University of North Carolina at Chapel Hill; North Carolina; In loco; USD 58.000 - 71.000; Tempo pieno

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Descrizione del lavoro

The UNC Eshelman School of Pharmacy’s Laboratory for Molecular Modeling (MML) seeks a Research Associate to advance computational methods and applications in drug discovery. You will collaborate on projects targeting intrinsically disordered proteins and help maintain software, databases and lab infrastructure.

Ideal candidates have a PhD in Medicinal Chemistry or related field with cheminformatics experience, and can contribute to machine learning and molecular modeling efforts within a dynamic

Competenze

• 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 collaboration with experimental colleagues.

Mansioni

• Support computational methodology development and applications to drug targets.
• Contribute to tool development and software maintenance in a multidisciplinary setting.
• Assist with organizing and maintaining laboratory software and databases.

Conoscenze

Computational chemistry

Cheminformatics

QSAR modeling

Molecular docking

Virtual screening

Team collaboration

Machine learning

Glide

AutoDock

Formazione

PhD in Medicinal Chemistry or related field

Strumenti

Glide

AutoDock

Descrizione del lavoro

Posting Information

Department SOP-CBMC - 452100

Career Area Research Professionals

Application Deadline 10/24/2026

Position Type Temporary Staff (EHRA NF)

Position Title Research Associate

Position Number 20079151

Vacancy ID N000901

Full-time/Part-time

FTE 1

Hours Per Week 40

Position Location North Carolina, US

Hiring Range $64,838

Proposed Start Date 12/04/2026

Estimated Duration of Appointment 12 months

Position Information

Be a Tar Heel!

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.

One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural, recreation and professional opportunities that span the campus and community.

University employees can choose from a wide range of professional training opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks that include numerous retail and restaurant discounts, savings on local child care centers and special rates for performing arts events.

Primary Purpose Of Organizational Unit

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.

Position Summary

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.

Minimum Education And Experience Requirements

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

Required Qualifications, Competencies, And Experience

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

Preferred Qualifications, Competencies, And Experience

Experience with manuscript preparation and submission

• Understanding of computational tools supporting the entire drug development workflow
• Familiarity with biological pathways

Campus Security Authority Responsibilities

Not Applicable.

Contact Information

Office of Human Resources Contact Information

If you experience any problems accessing the system or have questions about the application process, please contact the Office of Human Resources at [phone] or send an email to [e-mail]

Please note: The Office of Human Resources will not be able to provide specific updates regarding position or application status.

Equal Opportunity Employer Statement

The University is an equal opportunity employer and welcomes all to apply without regard to age, color, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, or sexual orientation. We encourage all qualified applicants to apply, including protected veterans and individuals with disabilities.