32 computer-programmer "Data driven Materials Modeling" Postdoctoral positions at Mathjobs.org

Tenure-Track Faculty Position in Mathematics for AI and Scientific Discovery (2027–2028)

discovery: AI-assisted simulation, surrogate modeling, inverse learning problems, automated scientific discovery, generative approaches for science, and data-driven discovery of mathematical or physical

2027 Luis W Alvarez and Grace M Hopper Postdoctoral Fellowships

the Computing Sciences Area and Berkeley Lab. Fellows apply advances in these fields to computational modeling, simulations, and advanced data analytics for scientific discovery in materials science

POSTECHCM2LAPOSTDOC

for real-world challenges, with applications from PDEs to materials science and climate modeling. • Geometry-Based Machine Learning (Group 2): Focuses on optimal transport, gradient-based

TMDC Postdoctoral Associate

computational methods and collaborate with translational scientists and clinicians to apply mathematical modeling to accelerate the development of novel therapies for cancer, neurodegenerative

Postdoctoral Researcher

mathematics Shira Faigenbaum-Golovin Manifold learning, shape space analysis, machine learning, mathematics of data science Mathematical modeling and manifold learning of high-dimensional data geometry

Postdoctoral Fellow

computational engineering, scientific and mathematical modeling, computational and applied mathematics, and computational visualization. In general, fellowship recipients collaborate in research under

Stanford Science Fellow

collaboratively with a diverse community of scholars. Stanford Science Fellows are an interdisciplinary community of exceptional postdoctoral scholars from around the globe whose work is driven by a sense of

Postdoctoral Associate

Position Overview: Successful candidates will join Roy Lederman's research group, which is affiliated with the Department of Statistics and Data Science (S&DS) and the Quantitative Biology Institute

Postdoctoral scholarship (1 year) in Discrete Mathematics

mathematics, financial mathematics, mathematical modeling, analysis, machine learning, optimization, mathematical foundations of artificial intelligence, mathematical ecology and mathematical statistics. UmeÃ

Postdoctoral Research Fellow: Computational Methods for Fluid-Granular Flows

tools to explore droplet migration, instability and gravity-driven flows within this setting. There is scope to bring your own perspective to the numerical approach, and your work will feed directly