Open positions, several PhD opportunities:
I’m launching a new lab at Purdue and recruiting several founding PhD students for Fall 2026. Topics include Bayesian & physics-based machine learning, uncertainty quantification, and interdisciplinary applications in mechanical and biomedical engineering. There will be opportunities to work on fundamental theory, develop new numerical methods, cross-departmental and international collaboration, and access to Purdue's newest supercomputer. I am seeking students with a background in computational, mechanical or biomedical engineering, physics, maths, computer science, or related, with in interest in computation and coding. The grad school application priority deadline is Dec 1st, 2025. Find the full announcement being released soon HERE. Please reach out to me, sranftl@purdue.edu, if you are interested.
Welcome!
I am an interdisciplinary scientist with focus on probabilistic and Scientific Machine Learning (SciML) and a physicist by training. Here is my Google Scholar and my ORCiD.
My research interests:
Scientific machine learning (AI4Science, AI4Engineering), Bayesian probability theory, uncertainty quantification, data analysis, scientific computing, computational physics & computational engineering. I am interested in theoretical foundations, methodological development and interdisciplinary applications in mechanical-, biomedical-, electrical-, civil-, computer-, and aerospace-engineering.
Short bio:
I am currently a postdoctoral fellow at Brown University, Division of Applied Mathematics.
Before that, I was a postdoctoral fellow at the Courant Institute of Mathematical Sciences, New York University, supported by an FWF Erwin-Schrödinger-Fellowship.
Before that, I was a Principal Investigator at TU Graz, Austria, at Graz Center for Machine Learning and Graz Center for Computational Engineering, and Visiting Scientist at the Munich Institute for Astro-, Particle and BioPhysics, Germany, and at Santé Ingénierie Biologie St-Étienne at École nationale supérieure des mines de Saint-Étienne, France. In that time, I have also co-founded the spin-off company arterioscope FlexCo for next generation predictive diagnostic intelligence from electrocardiographic signals.
Before that, I was a PhD student and then a postdoctoral associate at TU Graz, Austria, at the Institute of Theoretical & Computational Physics.
Before that, I did a Bachelor's + Master's in Engineering Physics at TU Graz, Austria.
Before that, I was a triathlete in physics olympiad, chemistry olympiad, and maths olympiad with a computer science hobby.