Postdoctoral Research Associate

Postdoctoral Research Associate

The Center for Drug Discovery, in association with the Bouve College of Health Sciences, Department of Pharmaceutical Sciences, and Professor Lei Xie seek to hire a Postdoctoral Research Associate to train in interdisciplinary projects involving developing new AI-driven Molecular Dynamics (MD) simulation methods and apply them to drug discovery in multiple disease areas. Preference will be given to applicants with prior training in Computer Science, Computational Biology, Computational Chemistry, and Computational Biophysics.

Extensive training opportunities cover all aspects of the drug discovery process. The Postdoctoral Research Associate will receive professional development training, gain valuable networking experience, and collaborate with scientists in The Center for Drug Discovery, Bouve College of Health Sciences, and the Institute of Experiential AI. They will also have access to personnel support, including graduate and undergraduate students, who will assist in conducting research projects.

Additionally, the research scientist will have the opportunity to lead manuscript and grant writing and submit publications as the primary author.

Minimum Qualifications:

• Ph.D. in Chemistry, Computer Science or equivalent
• In-depth knowledge and hands-on experience in MD simulation and molecular modeling
• Experience in processing and analyzing protein structure and chemical genomics data
• Familiar with use of high performance computing facilities
• Ability to communicate with experimental chemists and biologists
• Ability to develop research plans for executing strategy, data analysis/interpretation, and presentation of results
• Ability to work effectively in a highly integrated team environment
• Highly collaborative, self-motivated, and team-oriented individual
• Excellent written and oral communication skills and demonstrated ability to write peer reviewed quality work or invention disclosures for patent applications, technical reports.
• Consistent track record of accomplishments (e.g., peer-reviewed publications and/or patents).

Key Responsibilities & Accountabilities:

• Algorithm Development, Data Analysis and Communication:
• Effectively design, implement, and evaluate machine learning and computational methods
• Work with medicinal chemists for drug discovery projects
• Act as key member of a multidisciplinary drug discovery project team, assisting with development of project strategy, and analysis and communication of complex data
• Manage internal and external resources to deliver quality data in an efficient manner
• Maintain a broad awareness of the scientific and technological landscapes of Artificial intelligence, machine learning, omics data integration, systems biology, biophysics, and drug discovery and maintain knowledge of literature related to the areas of research pursued
• Scientific writing:
• Contribute to patent, report, grant, and scientific publication writing
• Training:
• Mentor and train junior team members
• Other:
• Foster a culture of scientific excellence, teamwork, and rigorous innovation

Position Type

Research

Additional Information

Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.

Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit for more information.

All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.

Compensation Grade/

Pay Type:

108S

Expected Hiring Range:

$60,315.00 - $85,192.50

With the pay range(s) shown above, the starting salary will depend on several factors, which may include your education, experience, location, knowledge and expertise, and skills as well as a pay comparison to similarly-situated employees already in the role. Salary ranges are reviewed regularly and are subject to change.