My professional journey

Download CV: here

Relevant Experience

PhD – Deep Learning-Driven Protein Design

Max Planck Institute of Biochemistry, Prof. Lukas Milles (Apr 2025 – present)

  • Developing DL-powered frameworks that integrate experimental feedback and modular design principles to boost protein stability and function.
  • Extending state-of-the-art generative models with active-learning loops and high-throughput biophysical assays.

Protein Design Deep Learning PyTorch Active Learning High-Throughput Screening Biophysics

Master’s Thesis in Molecular Dynamics Simulations

ETH Zürich, Prof. Sereina Riniker (Apr 2024 – Dec 2024)

  • Applied enhanced-sampling molecular dynamics to study cyclic-peptide permeability and structure-activity relationships.
  • Developed computational workflows integrating GROMACS, PLUMED, and RDKit.
  • Performed statistical-physics analyses to interpret simulation outcomes.
  • Proposed peptide variants with improved permeability profiles.

Molecular Dynamics (MD) Enhanced Sampling GROMACS PLUMED RDKit Computational Chemistry Statistical Physics

Internship – Machine Learning for Protein Design

AI4ProteinDesign Barcelona, Dr. Noelia Ferruz (Jun 2023 – Oct 2023)

  • Trained and optimized large language models to generate small-molecule-binding proteins.
  • Fine-tuned transformer architectures on HPC clusters.
  • Presented results at the 2nd European Rosettacon.

Machine Learning Protein Language Models Transformers HuggingFace HPC Git

Internship – Computational & Experimental Protein Design

EPFL Lausanne, Prof. Bruno E. Correia (Oct 2022 – Feb 2023)

  • Used AlphaFold- & proteinMPNN-driven sequence designs to create soluble analogues of membrane proteins.
  • Conducted medium-throughput protein expression and validated designs via X-ray crystallography and biophysical characterization (CD, SEC-MALS).
  • Generated soluble analogues retaining native scaffolds.

Structural Bioinformatics Computational Protein Design AlphaFold X-ray Crystallography CD Spectroscopy SEC-MALS Protein Expression

Internship – Protein Engineering

Max Planck Institute, Prof. Kai Johnsson (Nov 2021 – Jul 2022 & Mar 2023 – Jun 2023)

  • Characterized and engineered rhodamine-binding proteins for super-resolution microscopy.
  • Developed a user-friendly computational pipeline to optimize binding properties and stability.

Protein Expression Molecular Cloning Yeast Display ITC & FP Assays Molecular Docking

Education

M.Sc. Biochemistry

University of Heidelberg (2021 – 2024) – GPA 1.0 / 4.0
Focused on Computational Biology, Protein Design & Machine Learning

B.Sc. Molecular Biotechnology

University of Heidelberg (2018 – 2021) – GPA 1.3 / 3.7
Covered Biophysical Chemistry, Drug Research, Bioinformatics

Publications

  • “Computational design of soluble and functional membrane protein analogues” (Nature, 2024)
    Read Article | PDF

  • “An atlas of protein homo-oligomerization across domains of life” (Cell, 2024)
    Read Article | PDF

Conferences & Presentations

2nd European Rosettacon, Leipzig, Germany (Sep 2023)
Presented poster: “Mol2Pro: Generation of small-molecule-binding proteins using a pre-trained language model.”

Technical Toolkit

Python (advanced) PyTorch (advanced) GROMACS (intermediate) Bash/Linux (advanced) Git (advanced) HPC (Slurm, GPU) RDKit PyMOL / VMD

Scholarships & Awards

Apr 2022 – Dec 2024
German Academic Scholarship Foundation (Studienstiftung des deutschen Volkes)

Apr 2024 – Nov 2024
PROMOS Grant, University of Heidelberg

Jun 2023 – Oct 2023
ERASMUS+ Mobility Grant

Supervision & Engagement

  • Laboratory Supervisor (2021 – 2023): Organized and supervised drug-testing practical courses at Heidelberg University.
  • Biochemistry Student Council & Buddy Program (2021 – 2022): Coordinated mentorship for incoming international students.