Malte Mütter

Curriculum Vitae

Malte trained as an engineer before moving into biology. He studied Energy & Process Engineering and then Engineering Science at TU Berlin, working on fluid dynamics and mechatronics projects — from a test stand for a rotating blood pump to a bioreactor for studying antibiotic resistance evolution. That bioreactor project pulled him toward biology, and since 2020 he has been a PhD researcher in the Theoretical Biology group at ETH Zürich, studying how bacterial populations respond to multidrug treatment by combining high-throughput experiments with statistical and mathematical modeling. His PhD concludes in mid-2026, and he's now looking for the next role where that mix of quantitative modeling and applied science can do the most good.

Education

2020–2026

PhD

ETH Zürich

Thesis: "Experimental and Theoretical Investigations of Bacterial Population Dynamics Under Multidrug Treatment"

2017–2020

MSc Engineering Science

TU Berlin

Focus on fluid dynamics and mechatronics. Thesis: bioreactor design for resistance evolution (SolidWorks, STAR-CCM+).

2012–2017

BSc Energy & Process Engineering

TU Berlin

Thesis: test stand for a rotating blood pump, using particle image velocimetry (PIV) flow visualization.

Experience

07/2020–06/2026

PhD Researcher

ETH Zürich, Theoretical Biology group

Stochastic and deterministic models of bacterial population dynamics under multidrug treatment; time-series and imaging data analysis; teaching assistant for "Infectious Disease Dynamics" and "Evolutionary Ecology of Infectious Diseases"; published in PNAS and eLife.

11/2017–10/2019

Research Assistant

FU Berlin / Charité

Designed a bioreactor for antibiotic resistance evolution; secured start-up funding; co-supervised a bachelor's thesis; microcontroller-based control systems (Arduino, C++).

09/2016–09/2017

Undergraduate Research Assistant

TU Berlin

Experimental gas dynamics; Schlieren imaging; quantitative image analysis in MATLAB.

04/2016–06/2016

Research Internship

Charité – Universitätsmedizin Berlin

Control software for a blood-pressure measurement device (C++).

Skills

  • Modeling & Theory deterministic (ODE) and stochastic models of population dynamics; pharmacodynamic modeling (Hill functions, EC50, dose-response curves); drug interaction frameworks (Bliss independence, Loewe additivity); epidemiological modeling; model calibration and sensitivity analysis.
  • Statistics & Data Analysis time-series analysis of high-throughput trajectories (8640+ curves); functional data analysis; bootstrap inference; spline regression; uncertainty quantification; hypothesis testing.
  • Bayesian Modeling & Inference hierarchical Bayesian models; Hamiltonian Monte Carlo (NUTS) in PyMC; Gaussian Markov random fields; Bayesian random-effects meta-analysis; prior sensitivity analysis.
  • Experimental & High-Throughput large-scale 384-well plate experiments with liquid-handling robotics; multi-modal population measurement (luminescence, CFU, OD); bacterial culture and plasmid conjugation; experimental design.
  • Programming & Tools Python (NumPy, SciPy, pandas, statsmodels, matplotlib, PyMC), C++, MATLAB, Git, Linux, Docker.
  • Languages German (native), English (C2), Korean (A2–B1).