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Experience

ML Researcher (PhD Student & Postdoc)

University of Copenhagen, Denmark (2021–Present)

  • PhD in Biophysics at the Niels Bohr Institute (Kirkegaard Lab); currently a Postdoc at the IMAGE section, Department of Computer Science (DIKU).
  • Developed and optimized deep learning models for computer vision and reinforcement learning, with a focus on scalability and efficiency.
  • Specialized in distributed training, large-scale AI systems, and scientific ML workflows.
  • Designed full-stack ML pipelines from data preprocessing to deployment.
  • Published in top-tier journals including Nature Communications Biology, PNAS, and PRL.
  • 3-month external research stay at Imperial College London, working on computational modeling of biological systems.

Teaching Assistant

University of Copenhagen, Denmark (2020–2023)

  • Courses:
    • NDAB20001U: High Performance Programming & Systems
    • NDAB18003U: Elements of Machine Learning
    • NFYB14002U: Numerical Methods in Physics

Software Developer

Nucleids Applied Science, Barcelona (2018–2019)

  • Developed WPF C# applications for scientific computing in labs and nuclear environments.
  • Designed real-time monitoring and data analysis tools for particle detection systems.

Education

PhD in Biophysics

Niels Bohr Institute, University of Copenhagen (2021–2024)

  • Member of the Kirkegaard Lab
  • Dissertation: Mind the Gradient: Differentiable Computational Methods in Microorganism Behaviour Studies [link]

MSc in Computational Physics

Niels Bohr Institute, University of Copenhagen (2019–2021)

  • Thesis: Use of Tensor Processing Units (TPUs) in Physics Simulations [link]

BSc in Physics

University of Barcelona (2014–2019)

  • Minor: Theoretical Physics

Projects

Check out my GitHub for code from select research and OSS projects.
A full, curated list with descriptions is available here.

Publications

Peer-reviewed work in Nature Communications Biology, PNAS, PRL, and others.
See full list for citations, abstracts, and links here.

Technical Skills

  • Programming: Python, C++, C#, Fortran, Bash
  • Frameworks: JAX, PyTorch
  • Tools: Git, Docker, HPC, GPU/TPU
  • Specialties: Scientific Computing, Differentiable Programming, Deep Learning
  • Languages: English (Fluent), Spanish (Native), Catalan (Native)

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