With a PhD in Biomedicine and experience spanning academic research, industry, and European research infrastructures, I bring a dual focus on programme management and bioinformatics. I have coordinated multi-partner projects, delivered reporting and governance frameworks, and built reproducible data analysis in health science. My work bridges policy and practice, turning complex life-science data into clear, actionable outcomes for research institutes and companies alike.
Senior Science Officer - ELIXIR Europe January 2025 - Present
Support the ELIXIR Compute and Data Platforms by delivering technical contributions to the ELIXIR Scientific Programme and externally funded projects.
Coordinate multi-partner deliverables, risks and reporting across EOSC projects (ENTRUST, OSCARS, FIDELIS, STEERS).
Support development of trusted research infrastructures for sensitive health data; align ethics, security and interoperability.
Shape best practices for FAIR data, software sustainability, and open-science adoption across the ELIXIR network.
Contribute to grant proposals, impact frameworks and cross-programme integration.
Facilitate Open Science, data reproducibility, and software reusability across European life sciences by engaging with ELIXIR Nodes and stakeholders.
Conduct background research on emerging technologies, contribute to grant proposals, and provide scientific insights for ELIXIR’s research infrastructure.
Bioinformatician / Data Scientist - Prana-Tech, Ltd September 2023 - December 2024
Developed machine learning models to predict health outcomes.
Analysed health questionnaires and blood data to generate actionable insights.
Evaluated the feasibility of modelling approaches optimised for health data characteristics.
Integrated ML models into healthcare applications, ensuring functionality and usability.
Designed and implemented visualisation dashboards to improve data interpretability.
Project Manager / Junior Software Developer - PromptEquation, Lda September 2021 - December 2024
Managed 11 interdisciplinary projects through requirements analysis, budget optimisation and accurate documentation of customer requirements.
Developed in the Odoo framework and adapted Python scripts to fetch data from the server.
Developed and prepared different dashboards using open source tools (i.e. Apache Superset)
Used BI tools and dashboards to produce detailed reports for decision making.
Performed advanced database queries in PostgreSQL for data management and analysis.
Research Associate - Catholic University of Portugal September 2015 - August 2021
Performed MS-based proteomic analysis to characterise protein responses to SARS-CoV-2.
Performed advanced data analysis and visualisation using Python and R on genomic and proteomic datasets.
Developed custom software to store, analyse and visualise clinical data from NGS and MS sources.
Implemented COVID-19 saliva-based diagnostic protocols integrating genomic and proteomic data.
Assistant Lecturer - Catholic University of Portugal September 2020 - August 2021
Supported undergraduate classes to develop critical thinking and research skills.
Led laboratory sessions that combined hands-on experiments with computer-based bioinformatics learning.
Delivered results-oriented classes with practical applications in proteomics and molecular biology.
Helped establish industry–academia partnerships to give students real-world project experience.
Problem. Scale saliva testing efficiently in a regional network. Approach. Protocol development + platform for real-time data capture and role-based access; analytics in Python. Outcome. Validated pooling strategy and streamlined operations. Link. DOI: 10.1371/journal.pone.0263033
⚙️ SalivaPRINT Toolkit
Problem. Need for a standardised resource to profile salivary proteomes across conditions. Approach. Built a reference dataset (PRIDE submissions) + software toolkit for feature extraction and biomarker discovery. Outcome. Provided reusable resource; enabled comparative salivary proteomics studies. Link. DOI: doi:10.3390/jcm11195571
Problem. Lack of integrated tools for monitoring oral health data longitudinally, combining patient records, omics, and clinical observations. Approach. Co-founded the development of a platform to capture, store, and visualise oral health data in a reproducible and accessible way, aligning with FAIR principles. Outcome. Provided a foundation for digital oral health monitoring; contributed to ongoing research in oral disease progression and prevention.
🧬🦷 Oral Microbiome Profile in Clear Aligner Patients During Treatment
Problem. Limited knowledge of how orthodontic clear aligner therapy influences the oral microbiome composition. Approach. Collected saliva samples from patients undergoing aligner treatment; performed shotgun proteomics and 16S rRNA profiling with clinical metadata integration. Outcome. Identified temporal shifts in microbial communities and host–microbiome interactions during treatment, informing oral health monitoring and aligner therapy protocols. Link. DOI: Oral Microbiota in Caries Prevention, Diagnosis and Management - Challenges and Opportunities
🏠Industry Projects
📊 Prana-Tech (Health Data Modelling & Dashboards)
Problem. Clinicians lacked tools to evaluate patient data quality and compliance in real time. Approach. Designed dashboards (Superset/Metabase), integrated modelling feasibility studies on health questionnaires and blood data. Outcome. Shortened data-to-insight cycle; improved compliance monitoring and governance traceability.
⚙️ PromptEquation (ERP & Data Engineering)
Problem. SMEs needed custom ERP workflows and advanced reporting for operations. Approach. Python/Odoo development, PostgreSQL analytics, project management (requirements + budgets). Outcome. Delivered ERP modules and reproducible dashboards; reduced scope creep and improved reporting reliability.
Problem. Industrial process confirmation in assembly lines and workstations is often unreliable in environments with poor internet connectivity. Bosch Portugal set the challenge of creating an autonomous and automatic system that could overcome these constraints. Approach. Designed and prototyped a solution using Arduino Nano 33 BLE Sense sensors for proximity and condition monitoring, paired with an ESP32 watch for communication and user interaction. Two deployment modes were created:
Standalone mode with only Arduino Nano 33 BLE Sense for lightweight confirmation.
Hybrid mode combining Arduino + ESP32 for broader connectivity and user feedback. Outcome. Delivered a functional prototype during the Hackathon that demonstrated low-cost IoT feasibility for industrial process validation. The design was applicable across gravity-based assembly lines, manual progression lines, and fixed workstations. Event.Aveiro Tech City Hackathon 2024 · Bosch Portugal Challenge