PhD Opportunity | Data Science for Optical Biomarkers and Personalized Medi at iLoF

Porto, , Portugal -

Full Time

Start Date

Immediate

Expiry Date

05 Jun, 26

Salary

0.0

Posted On

07 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Signal Processing, Multimodal Modelling, Translational Health Data Science, Biomarker Discovery, Representation Learning, Uncertainty-Aware Prediction, Interpretable AI, Python, Statistics, Data Analysis, Time Series, Deep Learning, Bayesian Modelling, Causal Inference, Explainable AI

Industry

Biotechnology Research

Description

Company Description Hello! We are looking for a PhD candidate to help turn complex optical and biomedical data into robust digital biomarkers. Job Description This project will sit at the intersection of machine learning, signal processing, multimodal modelling, and translational health data science. It is designed for candidates who want to do rigorous doctoral research while working close to the experiments, samples, and decisions that shape real-world technology. Depending on the final work plan, the research may focus on biomarker discovery, representation learning, uncertainty-aware prediction, model robustness across cohorts or instruments, or interpretable AI for screening and stratification. About your role | What will you be doing? Analyse optical, experimental, and clinical datasets generated through iLoF’s platform and collaborations. Develop machine-learning and statistical models for classification, risk prediction, biomarker discovery, and representation learning. Build reproducible pipelines for preprocessing, validation, benchmarking, and uncertainty quantification. Investigate generalisation and robustness across instruments, sites, cohorts, or pre-analytical conditions. Collaborate closely with optics and assay teams to improve not only model performance, but also the way data is generated. Contribute to scientific publications, internal tools, and translational IP. Qualifications Qualifications MSc in Data Science, Physics, Mathematics, or a related field. Eligibility to enroll in a PhD programme. Strong Python skills and solid foundations in machine learning, statistics, and data analysis. Experience with physical signals, time series, multimodal datasets, or experimental data is highly valued. Comfort working in a multidisciplinary environment with scientists from non-data backgrounds. Nice to have Experience with deep learning, Bayesian modelling, causal inference, explainable AI, or MLOps. Familiarity with health data, biomarker modelling, or scientific machine learning. Interest in working close to experimental and clinical teams. Additional Information This is a strong opportunity for candidates who want their PhD to sit close to both the data and the underlying biology. At iLoF, you will be able to close the loop between models, experiments, and translational questions much faster than in a traditional academic setting. Additional Information iLoF in a nutshell 💡 As personalized medicine becomes the norm, scientists, patients, and healthcare systems worldwide face massive barriers in providing the right treatment to the right patient. Recognized by CB Insights and Financial Times as one of the most promising Digital Health companies in the world, iLoF is building an AI-powered platform capable of transforming precision medicine. Our goal is to become the platform that democratizes access to personalized medicine for millions of people living with complex diseases around the globe. Thanks to our proprietary optical fingerprint library of disease biomarkers and biological profiles we can offer personalized patient screening and stratification in a faster and more affordable way, saving up to 40% of the cost and 70% of the time while enabling a more human patient experience. Supported by leading institutions like Microsoft Ventures, Mayfield, and the Oxford University, iLoF is currently focusing on validating its platform technology in one of the biggest challenges of our times: Alzheimer's, while maintaining ongoing verticals on Digestive Cancer, Stroke, and Infectious diseases. Our Team 🧑🏻‍💻 We are a mix of scientists, entrepreneurs, and inventors based in Oxford and Porto, with a passion for healthcare! Recognized by CB Insights as one of the most promising Digital Health companies in the world and by the Financial Times as a Transformational Business in Healthcare, iLoF has been regularly featured in leading outlets like Tech Crunch, Wired, and Sifted and listed as a rising star in AI-Driven Drug Discovery, Health Screening & Data Analytics. What we value A Be Kind attitude is the main guideline within iLoF A hand in the hammer and another free to support your co-workers as a true team player An honest and egoless attitude towards discussions and critics working in good faith The braveness to speak your heart in any situation Through words or actions be always sure to make a difference at any moment! Be proud to drive your responsibilities to success and help others do the same, embracing ownership! Perks 😉 An exciting future with a deep-tech company selected by Financial Times and CB Insights as one of the most transformative companies in the world A high‑paced, flexible environment: adaptable working hours, strong remote work culture A stimulating atmosphere with room for creativity – fast‑paced, fun, and energetic start‑up with a friendly culture Weekly happy hours with amazing food and drinks Free coffee and snacks ☕ The opportunity to work with a world‑class, talented team – and potentially change healthcare as we know it for millions of patients living with complex diseases around the globe 🧑‍⚕️ We share a passion for being part of a mission that matters, and we are always looking for curious and collaborative people who share our values and want to be part of our journey. If that sounds like a fit for you, click the apply button and join us. You’ve read all this way but you’re missing a skill or two? No problem, it’s our job to upskill you to take your career to the next level. What we’re trying to say is, don’t be afraid to apply if you don’t tick all the boxes.

Responsibilities

The role involves analyzing optical, experimental, and clinical datasets to develop machine-learning and statistical models for classification, risk prediction, and biomarker discovery. Responsibilities also include building reproducible pipelines for validation and uncertainty quantification, and contributing to scientific publications.