Postdoctoral Fellow in Cancer Epidemiology
lorenzo.fabbri92sm@gmail.com | Madrid, Spain | lorenzofabbri.github.io/epilorenzo | ORCID | Google Scholar | GitHub | LinkedIn | Bluesky
Cancer epidemiology, causal inference, and evidence triangulation.
Postdoctoral Fellow Jun 2026 – Present
CNIO Madrid, ES
Genetic and Molecular Epidemiology Group. Causal inference and evidence triangulation applied to pancreatic and bladder cancer. Supervisor: Dr. Núria Malats.
Postdoctoral Fellow Oct 2025 – Mar 2026
Barcelona Institute for Global Health | Maternal, Child and Reproductive Health Barcelona, ES
Cancer genomics of vulvar and penile squamous cell carcinoma from whole-exome sequencing: somatic variant calling and copy-number analysis. Supervisor: Dr. Natalia Rakislova.
Predoctoral Researcher Jun 2021 – Sep 2025
Barcelona Institute for Global Health | Childhood and Environment Barcelona, ES
Early-life exposure to environmental chemicals and child neurodevelopment (HELIX, ATHLETE cohorts): causal inference, evidence triangulation, and multi-omic integration. Supervisor: Prof. Martine Vrijheid.
Student Research Assistant Mar 2017 – May 2017
Università della Svizzera italiana | Faculty of Informatics Lugano, CH
University Expert Diploma in Advanced Methods of Applied Statistics Dec 2025 – Sep 2026
Universidad Nacional de Educación a Distancia Madrid, ES
PhD in Biomedicine Sep 2021 – Sep 2025
Universitat Pompeu Fabra | Faculty of Medicine and Life Sciences Barcelona, ES
Thesis: Early Life Exposure to Environmental Chemicals and Neurodevelopment through Childhood and Adolescence. Supervisors: Prof. Martine Vrijheid and Dr. Léa Maitre. Grade: Sobresaliente cum laude.
M.Sc. in Quantitative and Computational Biology Oct 2017 – Oct 2019
Università degli Studi di Trento | CIBIO Trento, IT
Thesis (FBK, Trento): Machine Learning for Predictive Drug Induced Hepatotoxicity. Supervisors: Dr. Cesare Furlanello, Dr. Marco Chierici, and Prof. Enrico Domenici. Internship (HITS, Heidelberg): Machine and Deep Learning for Predictive Unbinding Kinetics of Kinases. Supervisors: Prof. Rebecca Wade, Dr. Daria Kokh, and Prof. Raffaello Potestio. Final mark: 110/110 cum laude.
M.Sc. Student in Computational Science Sep 2016 – Jul 2017
Università della Svizzera italiana | Faculty of Informatics Lugano, CH
Project (USI, Lugano): Investigation by Computational Techniques of Channelopathies Related to Sodium Channels. Supervisors: Prof. Vittorio Limongelli and Prof. Daniele Di Marino. (M.Sc. not completed; transferred to Università degli Studi di Trento.)
B.Sc. in Biotechnology Oct 2012 – Feb 2016
University of Parma | Dipartimento di Scienze Chimiche, della Vita e della Sostenibilità Ambientale Parma, IT
Thesis (RWTH, Aachen): Whole Body PBPK Modeling of Valproic Acid. Supervisors: Prof. Elena Maestri, Prof. Lars M. Blank, and Dr. Henrik Cordes. Final mark: 103/110.
Master’s Degree in the Analysis of Social Inequalities Oct 2026 – Present
UNED Madrid, ES
Master’s Degree in Economic Analysis Mar 2026 – Present
Universitat Oberta de Catalunya Barcelona, ES
Lifelong Learning Master’s in Public Health Dec 2025 – Present
UNED Madrid, ES
PG Certificate in Public Health Oct 2025 – Present
London School of Hygiene & Tropical Medicine London, GB
Basic Epidemiology (PHM101): grade 4/5.
Graduate Certificate in Theoretical Statistics and Probability Oct 2024 – Present
The Open University Milton Keynes, GB
Mathematical Statistics (M347): 91/100 with Distinction.
Montazeri P, Maitre L, Andrušaitytė S, Bjerve Gützkow K, Coufalíková K, Davidson R, Fabbri L, Grazuleviciene R, Guxens M, Heude B, Hjertager Krog N, Hoyles L, Karachaliou M, Sakhi AK, Keun HC, Klánová J, Lionis C, Margetaki K, McCartney AL, McEachan RR, Balcells C, Nawrot TS, Philippat C, Price E, Quentin J, Saulnier PJ, Slama R, Thomsen C, Urquiza J, Vorkas PA, Waiblinger D, Wright J, Yang TC, Vrijheid M. Update of the human early life exposome (HELIX) cohort: a European population-based exposome cohort—cohort profile. BMJ Open. 2026;16(8):e122608. doi:10.1136/bmjopen-2026-122608
Fabbri L, Andrušaitytė S, Basagaña X, Bhopal S, Bustamante M, Cheung RW, Gražulevičienė R, Guxens M, Kadawathagedara M, Kampouri M, Maitre L, Marquez S, Montazeri P, Myridakis A, Slama R, Thomsen C, Vrijheid M. Prenatal and childhood exposure to mixtures of environmental chemicals and adolescence attentional problems: a triangulation study. Environment International. 2025;206:109927. doi:10.1016/j.envint.2025.109927
Fabbri L, Robinson O, Basagaña X, Chatzi L, Gražulevičienė R, Guxens M, Kadawathagedara M, Sakhi AK, Maitre L, McEachan R, Philippat C, Pozo ÓJ, Thomsen C, Wright J, Yang T, Vrijheid M. Childhood exposure to non-persistent endocrine disruptors, glucocorticosteroids, and attentional function: A cross-sectional study based on the parametric g-formula. Environmental Research. 2025;264:120413. doi:10.1016/j.envres.2024.120413
Warkentin S, Stratakis N, Fabbri L, Wright J, Yang TC, Bryant M, Heude B, Slama R, Montazeri P, Vafeiadi M, Grazuleviciene R, Brantsæter AL, Vrijheid M. Dietary patterns among European children and their association with adiposity-related outcomes: a multi-country study. International Journal of Obesity. 2025;49(2):295-305. doi:10.1038/s41366-024-01657-6
Stratakis N, Anguita-Ruiz A, Fabbri L, Maitre L, González JR, Andrusaityte S, Basagaña X, Borràs E, Keun HC, Chatzi L, Conti DV, Goodrich J, Grazuleviciene R, Haug LS, Heude B, Yuan WL, McEachan R, Nieuwenhuijsen M, Sabidó E, Slama R, Thomsen C, Urquiza J, Roumeliotaki T, Vafeiadi M, Wright J, Bustamante M, Vrijheid M. Multi-omics architecture of childhood obesity and metabolic dysfunction uncovers biological pathways and prenatal determinants. Nature Communications. 2025;16(1):654. doi:10.1038/s41467-025-56013-7
Güil-Oumrait N, Stratakis N, Maitre L, Anguita-Ruiz A, Urquiza J, Fabbri L, Basagaña X, Heude B, Haug LS, Sakhi AK, Iszatt N, Keun HC, Wright J, Chatzi L, Vafeiadi M, Bustamante M, Grazuleviciene R, Andrušaitytė S, Slama R, McEachan R, Casas M, Vrijheid M. Prenatal Exposure to Chemical Mixtures and Metabolic Syndrome Risk in Children. JAMA Network Open. 2024;7(5):e2412040. doi:10.1001/jamanetworkopen.2024.12040
Fabbri L, Garlantézec R, Audouze K, Bustamante M, Carracedo Á, Chatzi L, González JR, Gražulevičienė R, Keun H, Lau CHE, Sabidó E, Siskos AP, Slama R, Thomsen C, Wright J, Yuan WL, Casas M, Vrijheid M, Maitre L. Childhood exposure to non-persistent endocrine disrupting chemicals and multi-omic profiles: A panel study. Environment International. 2023;173:107856. doi:10.1016/j.envint.2023.107856
Thiel C, Cordes H, Fabbri L, Aschmann HE, Baier V, Smit I, Atkinson F, Blank LM, Kuepfer L. A Comparative Analysis of Drug-Induced Hepatotoxicity in Clinically Relevant Situations. PLOS Computational Biology. 2017;13(2):e1005280. doi:10.1371/journal.pcbi.1005280
Master’s thesis Jun 2019 – Oct 2019
Fondazione Bruno Kessler | Data Science for Health Unit Trento, IT
Master’s internship Mar 2019 – May 2019
HITS | Molecular and Cellular Modeling Group Heidelberg, DE
Bachelor’s thesis Apr 2015 – Aug 2015
RWTH Aachen University | Institute of Applied Microbiology Aachen, DE
Juan de la Cierva Postdoctoral Fellowship Nov 2026 – Oct 2029
Agencia Estatal de Investigación
Causal Inference for Environmental Mixtures (CIBERESP) [declined] Jun 2024 – Sep 2024
Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública
Meritamente 2023 Mar 2024 – Sep 2024
Società Unione Mutuo Soccorso
Causal Inference for Environmental Mixtures (ATHLETE) [declined] Mar 2024 – Jun 2024
ATHLETE
Meritamente 2021 2022
Società Unione Mutuo Soccorso
Erasmus+ Traineeship Programme Scholarship Mar 2019 – May 2019
Università degli Studi di Trento
Faculty of Informatics Scholarship Sep 2016 – May 2017
Università della Svizzera italiana
Erasmus+ Traineeship Programme Scholarship Apr 2015 – Aug 2015
University of Parma
Student Tuition Waiver [declined] Jun 2024
CAUSALab Summer Courses on Causal Inference Boston, US
SNRN Best Abstract Award (Student Researchers) Sep 2022
International Society for Environmental Epidemiology Herndon, US
etverse: Modular R ecosystem for transparent causal inference [link]
Software | In development
Includes: causatr (causal effects estimation), negatr (negative control analysis), matchatr (matched case-control and case-cohort study analysis), and survatr (survival analysis).
bibaudit: Deterministic, Field-Level Verification of Bibliographies Against Crossref, DataCite and PubMed [link]
Software | PyPI, 2026
forrest: Publication-Ready Forest Plots [link]
Software | CRAN, 2026
orcidtr: Retrieve Data from the ORCID Public API [link]
Software | CRAN, 2026
See github.com/lorenzoFabbri/talks for slides and materials.
Transparent causal inference for observational epidemiology
Invited talk | Colicino Group, Icahn School of Medicine at Mount Sinai (via Zoom), Jan 2025
A precision environmental health approach to childhood obesity and metabolic dysfunction: identifying biological pathways and prenatal determinants [link]
Stratakis N, Anguita Ruiz A, Fabbri L, et al.
Poster | ISEE Conference Abstracts, 2024
Prenatal Exposure to Chemical Mixtures and Metabolic Syndrome Risk in European Children [link]
Güil Oumrait N, Stratakis N, Maitre L, …, Fabbri L, et al.
Poster | ISEE Conference Abstracts, 2024
Childhood exposure to non-persistent endocrine disrupting chemicals and multi-omic markers in a population-based child cohort [link]
Fabbri L, Garlantezec R, Chatzi L, et al.
Poster | ISEE Conference Abstracts, 2022
Childhood exposure to non-persistent endocrine disrupting chemicals and multi-omic markers in a population-based child cohort [link]
Fabbri L, Garlantezec R, Thomsen C, et al.
Poster | EURION Cluster Annual Meeting, 2022
Childhood exposure to non-persistent endocrine disrupting chemicals and multi-omic markers in a population-based child cohort [link]
Fabbri L, Garlantezec R, Thomsen C, et al.
Poster | PPTOX-VII International Conference, 2022
Efficient and Portable MPI Support for Approximate Bayesian Computation [link]
Fabbri L, Ummadisingu A, Dutta R, et al.
Poster | Platform for Advanced Scientific Computing, 2017
Systematic Review, Meta-Analysis, and Evidence Synthesis Using Model Selection Jul 2026
GESIS - Leibniz Institute for the Social Sciences Mannheim, DE
Codechella May 2026
Mixtape Sessions Madrid, ES
Spring School in Causal Inference with Observational Data Apr 2022
Causal Insights Leeds, GB
Computational Bayesian methods using brms in R Feb 2022
Physalia Courses Berlin, DE
ELIXIR Omics Integration and Systems Biology Sep 2021
National Bioinformatics Infrastructure Sweden Uppsala, SE
Advanced Statistics: Statistical Modelling Aug 2021
Swiss Institute of Bioinformatics Lausanne, CH
Alpine Exposome Summer School Jun 2021
INSERM Paris, FR
Metabolomics Data Processing and Data Analysis Feb 2021
University of Birmingham Birmingham, GB
Mendelian Randomisation May 2020
Imperial College London London, GB
Image Analysis and Modeling of Complex Biological Dynamics Sep 2017
University of Würzburg Würzburg, DE
Effective High Performance Computing Summer School Jul 2017
CSCS - Swiss National Supercomputing Centre Lugano, CH
MARVEL School on Variationally Enhanced Sampling Feb 2017
Università della Svizzera italiana Lugano, CH
Advanced Course in Alternatives to Animal Experimentation Nov 2015
University of Genoa Genoa, IT
Students and New Researchers Network 2022 – 2023
International Society for Environmental Epidemiology Herndon, US
Early Career Scientist Working Group 2022
Consortium of Metabolomics Studies (COMETS) Bethesda, US
| Category | Details |
|---|---|
| Languages | Italian (native), English (C1, IELTS 7.0), Spanish (basic) |
| Programming | R, Python, Bash, MATLAB, C |
| Markup | LaTeX, Quarto/RMarkdown |
| Tools | git, SLURM, high-performance scientific computing |
| Methods | causal inference (g-methods, negative controls, trial emulation, Mendelian randomization), longitudinal/panel data analysis, survival analysis, multi-omic integration |
Last updated: October 2026