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Curriculum Vitae

Mara Ellison Voss · Postdoctoral Researcher

m.voss@example.eduZürich, Switzerland

Appointments

2022 – present

Postdoctoral Researcher

Institute for Theoretical Neuroscience, ETH Zürich · Zürich, CH

Modelling uncertainty representation in cortical circuits; mentoring two doctoral students.

  • Led the population-geometry project across two labs (5 people).
  • Secured an SNSF Spark grant for uncertainty benchmarking.
2020

Research Intern

DeepMind · London, UK

Structured latent models for scientific time-series data.

Education

2018 – 2022

PhD, Computational Neuroscience

Gatsby Unit, University College London · London, UK

Thesis: Latent variable models for large-scale neural population activity. Advised by Prof. J. Hartwell.

2016 – 2018

MSc, Machine Learning

University of Edinburgh · Edinburgh, UK

Distinction. Dissertation on variational inference for time series.

2013 – 2016

BSc, Physics

University of Bristol · Bristol, UK

First-class honours.

Publications

  1. 2025 · journal

    The geometry of uncertainty: curved manifolds in cortical population codes

    M. E. Voss, R. Nakamura, D. Feldmann

    Nature Neuroscience

    pdf / code / data / doi

  2. 2024 · conference

    Amortized inference for high-dimensional electrophysiology with structured priors

    M. E. Voss, A. Kowalski

    NeurIPS

    pdf / code

  3. 2024 · preprint

    When do linear readouts fail? A stress test for neural decoding

    M. E. Voss, D. Feldmann, S. Ortega

    arXiv

    arXiv

  4. 2023 · workshop

    Temporal scaling in recurrent representations of interval timing

    S. Ortega, M. E. Voss

    Cosyne (Workshop)

    poster

Awards

2024

SNSF Postdoc.Mobility Fellowship

Swiss National Science Foundation

2022

Outstanding Thesis Award

UCL Faculty of Life Sciences

2019

Cosyne Presenter Travel Award

Computational and Systems Neuroscience

Teaching

2023, 2024

Co-lecturer — Probabilistic Machine Learning

ETH Zürich (MSc)

2019 – 2021

Teaching Assistant — Statistical Inference

UCL (MSc)

Skills

Languages

Python · TypeScript · Julia · C++ · R · MATLAB

Frameworks

JAX · PyTorch · NumPy / SciPy · React · scikit-learn

Methods

Variational inference · Dynamical systems · GLMs · Dimensionality reduction · Bayesian modelling

Languages

English — native · German — B2 · French — B1