47 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" Postdoctoral positions at Argonne
Sort by
Refine Your Search
-
campus in Lemont, Illinois five days per week. Preferred Qualifications Proficiency in programming (e.g., Python) for advanced data analysis, machine learning, and computer vision to accelerate insights
-
collaboration with team members. Skilled written and verbal communicator, including the ability to present complex information so that it is understandable to a broad audience. Computer skills relevant for data
-
skills and familiarity with LLM APIs (e.g., OpenAI API), agent frameworks (e.g. LangChain), PyTorch, and the Python scientific stack (e.g., numpy, pandas, scikit-learn). Experience with front-end
-
; experience with machine learning is a plus Demonstrated record of peer-reviewed publications Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Qualifications
-
microelectronics project. To learn more: Argonne to lead two microelectronics research projects under U.S. Department of Energy initiative | Argonne National Laboratory Position Requirements Recent or soon-to-be
-
reinforcement learning Experience with high-performance computing, physics-based simulations, and multimodal data workflows Demonstrated ability to train and deploy AI/ML models using simulated and experimental
-
Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
-
or equivalent. Knowledge and experience with analytical techniques such as XRD and SEM. Skill in devising and performing experiments to acquire data, using and maintaining research equipment, compiling
-
to analytical techniques for characterizing electrolytes using UV-VIs absorption spectroscopy, ICP-MS, LC-MS, GC-MS, and ICP-MS. This position will include learning experimental workflows and adapting them
-
cells and electrolyzers is welcomed. Experience with statistical analysis methods such as PLS-DA, supervised learning and database building are highly encouraged. The applicant is expected to think and