EMBO Postdoctoral Associate · Fakhri Lab, MIT
Tom Burkart
I study how order and time-irreversibility emerge in non-equilibrium biological systems: combining statistical physics, high-dimensional data analysis, and machine learning to understand the physics of living matter.
About
I'm a physicist working at the interface of theory and biology. My PhD, supervised by Erwin Frey at LMU Munich, focused on self-organization in biological systems, specifically intracellular protein pattern coupled to dynamic cell geometries. As a postdoc in the Fakhri Lab at MIT, supported by an EMBO Postdoctoral Fellowship, I now work on representation learning of high-dimensional non-equilibrium complex systems, combining theory, data analysis, and machine learning.
I'm currently looking to bring these tools — statistical modeling, machine learning, and large-scale data analysis — to applied problems in health and biotech, where they can translate research insight into real-world impact.
Skills
I also co-develop open-source teaching materials — including a set of Jupyter notebook tutorials on simulating pattern formation in cells, written for the 2022 Q-Life Winter School in Paris with Jan Kirschbaum and David Zwicker.
Research & Publications
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Light-induced cortical excitability reveals programmable shape dynamics in starfish oocytes
"With these switches, we were able to arbitrarily modulate the protein distribution in the cell through light stimuli, which led to deformations."
In the press: MIT News · ORIGINS Cluster · Nature Physics Research Briefing
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Dimensionality reduction in bulk-boundary reaction-diffusion systems
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Mechanochemical feedback loop drives persistent motion of liposomes
"The two-component bacterial MinDE protein system is the simplest biological pattern-forming system ever reported. Now, it establishes a mechanochemical feedback loop fuelling the persistent motion of liposomes."
In the press: Nature Physics News & Views
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Periodic temporal environmental variations induce coexistence in resource competition models
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Control of protein-based pattern formation via guiding cues
Talks
Invited Colloquia
"Skip the Sweep — Learning What Matters in Models of Living Systems"
A look at how contrastive embedding methods can help identify the observables that actually matter when analytical approaches to non-equilibrium biological systems fall short — with preliminary results from a toy model.
"Chemomechanical Self-Organization Across Scales in Living Systems"
Invited colloquium given on receiving the Arnold Sommerfeld Center PhD Prize.
Selected Conference Talks
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"From Aggregate to Organism: Emergence of Multicellularity in Sea Sponges"
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7th International Conference on Physics and Biological Systems (PhysBio 2024)
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DPG Spring Meeting
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STATPHYS28 — 28th International Conference on Statistical Physics
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ICBP 2023 — 11th International Conference on Biological Physics
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"Light, Proteins, and Shape: Exploiting Pattern Formation for Light-Controlled Cell Deformations"
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DPG Spring Meeting
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Turing Symposium
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DPG Spring Meeting
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"Enhanced Biodiversity in Time-Dependent Environments"
Awards & Fellowships
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EMBO Postdoctoral Fellowship
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Arnold Sommerfeld Center PhD Prize — LMU Munich
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CeNS Publication Award for Best Interdisciplinary Publication — Center for NanoScience, LMU Munich
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Add-On Fellowship for Interdisciplinary Life Science — Joachim Herz Stiftung
Experience & Education
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Postdoctoral Researcher — Fakhri Lab, MIT
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Co-Organizer — MIT Hacking Medicine
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PhD Statistical and Biological Physics — LMU Munich
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Junior Consultant — Basycon Unternehmensberatung GmbH
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MS Biophysics — LMU Munich
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BS Physics — LMU Munich
Contact
Cambridge, Massachusetts