Postdoctoral Appointee - Virtual Drug Response Prediction
Requisition Number: 405841 Location: Lemont, IL
Functional Area: Research and Development Division: LCF-Leadership Computing Facility
Employment Category: Temporary 6 Months or Greater Education Required: Doctorate Degree
Level (Grade): 700 Shift: 8:30 - 5:00 Share: Facebook LinkedIn Twitter
We invite you to apply for a Postdoctoral Appointee position with our Leadership Computing Facility Division (LCF).
In this role you will:
- Research and develop generative models for drug design and predictive models for drug response that can be used to optimize pre-clinical drug screening and drive precision medicine-based treatments for cancer patients.
- Deep learning methods will include generative models and autoencoders, with the goal to enable billions of virtual drugs to be screened, singly and in combinations, predict their effects on tumor cells, and quantify uncertainty in predictions.
- The position is with a project under ALCF's Aurora Early Science Program, which combines the efforts of multi-institutional investigator teams with ALCF staff and Aurora vendor applications experts.
We expect you to have:
- A PhD + 0-3 years in computational sciences including biology, engineering, or in a related field.
- Comprehensive knowledge of numerical methods, parallel programming, machine learning/deep learning methods and frameworks.
- Comprehensive experience programming in one or more programming languages such as C, C++, and Python.
- Considerable knowledge of parallel algorithms, distributed memory architectures, and parallel performance evaluation of domain specific implementations.
- Ability to create, maintain, and support high-quality software.
- An ideal candidate would have published their scientific software in a public repository (e.g. GitHub)]
- Strong communication skills both verbal and written.
- Independent judgment and critical thinking.
As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.