Research Associate

University-of-North-Carolina-At-Chapel-Hil; Chapel Hill (NC); On-site; USD 70,000 - 95,000; Full time

Job summary

The Laboratory for Molecular Modeling (MML) at the UNC Eshelman School of Pharmacy seeks a Research Associate to support computational methodology, tool development and applications to drug targets. You will join a multidisciplinary team and assist with development projects and applications studies, especially for intrinsically disordered protein targets as primary responsibility.

The role includes some lab organization and maintenance tasks, such as software, databases, and general lab-space

Qualifications

• PhD in Medicinal Chemistry or related field with strong evidence of cheminformatics.
• 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.

Responsibilities

• Support development projects and applications studies for drug targets.
• Maintenance and upkeep of laboratory software, databases, and general lab space.

Skills

Computational chemistry

Cheminformatics

QSAR modeling

Molecular docking

Hit-to-lead optimization

Virtual screening

Machine learning

Glide

AutoDock

Multidisciplinary teamwork

Presentations and manuscripts

Education

PhD in Medicinal Chemistry or related field

Post-baccalaureate degree

Tools

Glide

AutoDock

Job description

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

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.

Optional and Required Documents

• Required Documents Curriculum Vitae / Resume
• Optional Documents List of References

Supplemental Questions

Required fields are indicated with an asterisk (*).

• * Please select the response below that describes your level of education that best or most closely satisfies the education requirements for this position.
  • Bachelor’s degree in required discipline(s) listed or related field
  • Bachelor's degree in any field/discipline
  • Master's degree or Doctorate degree in required discipline(s) listed or related field
  • Master's degree or Doctorate degree in any field/discipline
  • None of the above