Sort by
Refine Your Search
-
beyond the Standard Model, including effective field theories and perturbative QCD, phenomenology at current and future colliders, as well as emerging areas in Artificial Intelligence, Machine Learning
-
clustering, redshift-space distortions, weak/strong gravitational lensing, and artificial intelligence/machine learning (AI/ML). The observational focus is on optical sky surveys (DES, DESI, Roman, Rubin Obs
-
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
-
. Additionally, the CPS provides an interdisciplinary home for spawning simulation programs and projects, often in collaboration with the ALCF. The ALCF and CPS division are seeking a postdoctoral appointee to
-
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
-
and unravel structure-function relationships. This position is suited for a highly energetic and self-driven researcher willing to work in highly collaborative teams. This position will involve a
-
collaborating with a software engineering team to translate research into production-ready tools. The successful candidate will be part of an inter-lab, highly inter-disciplinary team of experts in ML, applied
-
The Data Science and Learning Division (DSL) at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting edge molecular and microbiology work to enhance non-proliferation
-
, datasets, and risk monitoring tools in collaboration with DOE national laboratories and federal partners. Prepare detailed reports and briefings on methodologies, analyses, and findings. Collaborate with
-
visualization systems using realistic scientific data and simulations, including applications in cosmology, materials, fusion, environmental science, and light source data Collaborate closely with domain