Postdoctoral Appointee – Physics-Aware Multimodal Deep Learning
| Company | Argonne National Laboratory |
|---|---|
| Location | Woodridge, IL, USA |
| Salary | $70758 – $110379.55 |
| Type | Full-Time |
| Degrees | PhD |
| Experience Level | Junior |
Requirements
- PhD in a relevant field completed in the past 5 years or soon to be completed.
- Knowledge of x-ray/optical/electron physics, including diffraction, optics, detectors, scattering etc.
- Experience with deep learning (DL) libraries such as Tensorflow, PyTorch, JAX etc.
- Experience with physics-informed neural networks, automatic differentiation, neural ODEs, or other physics-aware DL techniques.
- Skill in programming languages such as Python, C/C++, Go, Rust etc.
- Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
Responsibilities
- Develop physics-aware multi-modal deep learning methods that are broadly applicable across the physical sciences but applied initially to x-ray characterization needs.
- Publish results in high impact journals.
- Present at conferences.
- Work with the software engineering team to translate the models into production.
Preferred Qualifications
- Experience with version control such as Git and collaborative software development.
- Experience with uncertainty quantification and multi-modal deep learning.
- Experience with distributed training.
- Skill in written and oral communications.
- Experience interacting with scientific staff and research groups. Ability to work effectively as a member of a team. Ability to effectively communicate with people of different backgrounds and skill sets.