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Education

PhD in Biomedical Sciences — Universidad Nacional Autónoma de México (UNAM), Neurobiology Institute, Juriquilla, Querétaro, Mexico — 2019–2023 Thesis: “Excitability evaluation in a cortical dysplasia rodent model.” Supervisor: Luis Concha

BSc in Biology — Universidad Nacional Autónoma de México (UNAM), Faculty of Sciences, Mexico City — 2014–2018 Thesis: “Characterization of the cellular network of lactotrophs and thyrotrophs during the reproductive cycle in a rodent model.” Supervisor: Tatiana Fiordelisio Coll

Experience

Postdoctoral Researcher — CNRS, Institut de Génomique Fonctionnelle, Montpellier, France — Apr 2024–Mar 2026

  • Conducted research involving computational neuroscience, data analysis, and biological data interpretation.
  • Applied Python, machine learning, deep learning, image analysis, and time-series analysis to neuroscience research.
  • Worked with large datasets and developed computational approaches for biological and neuroscience questions.

Postdoctoral Fellow / Ingénieure Biologiste en analyse des données — CNRS, Institut de Génomique Fonctionnelle, Montpellier, France — Sep 2023–Mar 2026

  • Conducted data analysis and computational research in neuroscience and neuroendocrinology.
  • Applied computational methods to biological data, including image analysis and quantitative analysis.
  • Participated in scientific research and experimental design.

Research Assistant / PhD Student — UNAM, Institute of Neurobiology, Juriquilla, Querétaro, Mexico — Jan 2018–Sep 2023

  • Designed and conducted experiments using rodent models.
  • Performed data acquisition and analysis for neuroscience research.
  • Worked on cortical dysplasia and brain connectivity research.
  • Taught postgraduate students about the research project and experimental methods.

Visiting PhD Candidate — UNAM, Cellular Physiology Institute, Mexico — Jan 2023–Aug 2023

  • Analyzed electrophysiological data using population dynamics, machine learning, deep learning, and information theory approaches.

Skills

  • Programming: Python
  • Computational methods: Computational neuroscience, machine learning, deep learning, time-series analysis, large dataset management
  • Neuroscience: Neurobiology, calcium imaging in vitro, miniscope recordings, non-human EEG datasets, MRI analysis
  • Experimental techniques: Animal surgery, stereotaxic surgery, immunofluorescence, viral tracing
  • Data & imaging: Image analysis, experimental design
  • Scientific: Scientific writing, scientific illustration, science communication, open science
  • Spoken languages: Spanish (native), English (proficient), French (proficient), Portuguese (intermediate)

Awards & Grants

  • 2019–2023 — CONACyT Graduate Scholarship, Mexican National Council for Science and Technology
  • 2023–2026 — FRM Fondation pour la Recherche Médicale Postdoctoral Researcher, Institut de Génomique Fonctionnelle, CNRS, Montpellier, France
  • 2024 — GroPro Travel Award (poster), Stirling, UK
  • 2020 — Scholarship to LASCON Computational Neuroscience School, USP, Brazil
  • 2017–2018 — Scholarship for International Research Internship, UNAM
  • 2020 — NEUBIAS Workshop in Bioimage Analysis, Institut Pasteur, France

Teaching & Mentoring

  • Professional Career Mentor, Neuromatch Computational Neuroscience School — 2026
  • Supervised Olimpia Ortega-Fimbres, MSc Student, Institute of Neurobiology, Querétaro — 2022–2023
  • Supervised Daniela Bravo-Coutiño, BSc Student, Institute of Neurobiology, Querétaro — 2022–2023
  • Supervised Paulina Villaseñor de la Barrera, MSc Student, Institute of Neurobiology, Querétaro — 2021–2023
  • Supervised David Cortés-Servin, MSc Student, Institute of Neurobiology, Querétaro — 2020–2021

Publications

  • Aquiles, A., Pinedo, L., Regalado, M., Luna-Munguia, H., Peña-Ortega, F., Concha, L., & Rossi-Pool, R. (2026). Assessing the degree of cortical dislamination through electrical pattern analysis. iScience, 29(6).

  • Aquiles, A., Aparicio Arias, J., Lafont, C., Hodson, D., Santiago-Andres, Y., Mollard, P., & Fiordelisio, T. (2026). Population geometry reveals directed coupling and transient bistability in spontaneous pituitary secretion. bioRxiv. Under revision in Nature Communications Physics.

  • Santiago-Andres, Y., Aquiles, A., Taniguchi-Ponciano, K., Salame, L., Guinto, G., Mercado, M., & Fiordelisio, T. (2024). Association between Intracellular Calcium Signaling and Tumor Recurrence in Human Non-Functioning Pituitary Adenomas. International Journal of Molecular Sciences, 25(7), 3968.

  • Aquiles, A., Fiordelisio, T., Luna-Munguia, H., & Concha, L. (2023). Altered functional connectivity and network excitability in a model of cortical dysplasia. Scientific Reports, 13(1), 12335.

  • Aquiles, A., Mollard, P. (2025). Uncovering baseline pituitary states. Early Career Perspective.Under revision in Journal of neuroendocrinology.

  • Villaseñor, P. J., Cortés-Servín, D., Pérez-Moriel, A., Aquiles, A., Luna-Munguía, H., Ramirez-Manzanares, A., et al. (2023). Multi-tensor diffusion abnormalities of gray matter in an animal model of cortical dysplasia. Frontiers in Neurology, 14, 1124282.

Scientific Communication

  • Co-founder of the science communication student group Neurokuni at the Institute of Neurobiology — 2021–2022.
  • Writing, structure, and direction of the science communication video Savage Brains during Brain Week at the Institute of Neurobiology, UNAM — 2020.
  • Writing and structuring podcast episodes for NEUROKUNI on Spotify.
  • Plenary talk at Talent Land, Guadalajara, Mexico — 2019: How to detect science fake-news in a technology era.
  • Workshop for children: I want to be an insect — Mexico City, 2018.
  • Workshop for teachers: Neurobiology of lies — ISSSTE, Mexico City, 2020.

Peer Review

  • Frontiers in Computational Neuroscience — Reviewer
  • Biomarker Research — Reviewer