Post Doctorate RA - Computational Chemistry, Machine Learning
The Computational Biology group within the Environmental and Biological Sciences Directorate at PNNL-Battelle has a postdoctoral opening with strong expertise in computational chemistry, Artificial Intelligence (AI) and Machine Learning (ML). The candidate will be involved in cutting-edge research focused on computational chemistry and cheminformatics, in particular, to automate physics-based molecular modeling simulations to predict key features of small molecules with potential application in developing drug therapeutics. The incumbent will assist in computational tool development for fully autonomous design, work directly in interdisciplinary teams including chemists, bioinformaticians, computer scientists, data scientists and software developers. The position involves working with high-performance computing platforms, statistical analysis, and data integration methods that will be used to develop artificial intelligence tools for high throughput molecule design. The successful candidate must be able to collaborate, identify scientific problems and opportunities, and leverage concepts and tools including recent advances in deep learning, to develop data driven computational solutions. The research associate will contribute to large, multidisciplinary research programs focused on fundamental and biological sciences and will be part of the Computational Biology and Bioinformatics group.
Qualifications, Skills, and/or Training Necessary for Position:
- Ph.D. in computational chemistry/physics, computer science, medicinal chemistry, or related discipline.
- Strong expertise in molecular dynamics simulations, docking algorithm, PK/PD, ADME/Toxicity. Develop software stack for automating a computational pipeline.
- Familiarity with several machine learning algorithms and packages (unsupervised/supervised/reinforcement learning, active learning, neural networks, NLP and SVM).
- Experience with Unix/Linux, HPC environments, and experience with a scripting and programming language (e.g. Python, C/C++ etc).
- Expertise in the design, execution of algorithmic solutions for curation, analysis, mining, and modeling of chemical and biological data.
- Strong track record of research accomplishment and publications/presentations
- Strong communication skills and enthusiasm for working individually and in an interdisciplinary team environment.
Minimum Qualifications
Candidates must have received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university.
Preferred Qualifications
- Solid foundation in computational chemistry/biology for physics-based modeling and computer science with AI/ML expertise for data integration to predict patterns/features that are useful for new experiment design.
- Excellent expertise in applying a combination of multiple techniques including biophysical modeling/simulations and AI/ML to generate innovative ideas and robust computational solutions for compound design.
- Experience in manipulating and analyzing large datasets and with visualization of complex data types.
- Strong organizational skills with the ability collaborate with internal/external researchers. Demonstrated ability to work in a multidisciplinary team.
Equal Employment Opportunity
Battelle Memorial Institute (BMI) at Pacific Northwest National Laboratory (PNNL) is an Affirmative Action/Equal Opportunity Employer and supports diversity in the workplace. All employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, marital or family status, sexual orientation, gender identity, or genetic information. All BMI staff must be able to demonstrate the legal right to work in the United States. BMI is an E-Verify employer. Learn more at jobs.pnnl.gov.
If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via https://jobs.pnnl.gov/help.stm
Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.