Mechanistic models allow to make precise and testable predictions about the underlying biophysical mechanisms that influence neural activity.
Jonas Beck
Jonas Beck is interested in probabilistic inference in mechanistic models of neuroscience. More specifically, he applies probabilistic numerical methods and simulation-based inference to fit Hodgkin-Huxley models to observed (experimental) data as part of the PIMMS Network Project of the Cluster of Excellence - Machine Learning for Science.
Mechanistic models allow to make precise and testable predictions about the underlying biophysical mechanisms that influence neural activity.
Present Positions And Title
PhD Student
Research Group
Email Address
Phone
Career
| Period | Institution | Role |
|---|---|---|
| Since 2022 | University of Tübingen & IMPRS-IS | PhD student |
| 2020 | University of Tübingen, Berens & Macke lab | Lab Rotation |
| 2020 | University of Tübingen, Levina lab | Lab Rotation |
| 2019 | Sultan Qaboos University, Muscat, Oman | Research assistant |
Academic Education
| Year | Degree | Institution | Field of Study |
|---|---|---|---|
| 2019 - 2021 | M.Sc. | University of Tübingen | Neural Information Processing |
| 2015 - 2019 | B.Sc. | University of Potsdam | Physics |