Principal Scientific Lead (Biophotonics & Data Analytics)

Location: Hybrid, London, United Kingdom

Employment type: Full-time

Company

hirify.global is a deep-tech digital health company building an AI-powered optical fingerprint platform for personalized medicine, disease biomarker discovery, screening, and patient stratification.

What you will do

• Set standards for preprocessing, modelling, validation, robustness assessment, and overfitting control for high-dimensional spectral data with small clinical sample sizes.
• Select and develop chemometric, dimensionality-reduction, regularized, Bayesian, physics-informed, self-supervised, metric-learning, and transfer-learning methods where appropriate.
• Design data augmentation, domain-adaptation, experiments, and laboratory protocols using physically grounded synthetic spectra without introducing bias or leakage.
• Interpret optical signatures from plasma and nanoparticle samples, diagnose baseline drift, autofluorescence, scattering, and instrument variability, and assess physical instrument variables before applying algorithmic fixes.
• Lead scientific relationships with CROs, contractors, academic groups, and university principal investigators, including statements of work, data and code standards, deliverable review, and IP protection.
• Act as the senior scientific partner to the Head of Innovation, mentor scientists and data scientists, and shape the technology roadmap and long-term technology bets.

Requirements

• PhD in biophotonics, computational physics, chemometrics, applied mathematics, or a closely related quantitative field.
• Either 5–8+ years after the PhD delivering R&D outcomes in industry, a deep-tech start-up or scale-up, scientific consultancy, or translational research, including leading technical work through to a product, validated method, or clinical study; or 8+ years of post-PhD research with a strong relevant publication record and leadership of major projects such as principal or co-investigator roles on large funded programmes or multi-partner consortia.
• Proven experience building predictive models on real instrument-generated data, ideally spectral or optical, with tightly constrained sample sizes; simulated or standard benchmark datasets alone are insufficient.
• Deep expertise in chemometrics and statistical learning for high-dimensional, correlated data, including rigorous validation and prevention of data leakage.
• Strong Python, including tools such as NumPy, SciPy, scikit-learn, and PyTorch, with an emphasis on transparent and reproducible analysis.
• Experience setting scientific direction for others and managing external scientific partners or contractors.

Nice to have

• Experience with blood plasma or other biofluid spectroscopy.
• Experience with physics-informed machine learning, self-supervised learning, metric learning, or domain adaptation.
• Exposure to diagnostics, IVD, or regulated product development.

Culture & Benefits

• Flexible, high-paced environment with adaptable working hours and a strong remote work culture alongside the hybrid workplace.
• Collaborative, friendly start-up culture focused on kindness, teamwork, honest discussion, courage, ownership, and helping colleagues succeed.
• Opportunity to work on an AI-powered healthcare platform addressing Alzheimer's, digestive cancer, stroke, and infectious diseases.
• Weekly happy hours, food and drinks, free coffee, and snacks.
• Work with scientists, entrepreneurs, and inventors based in London and Porto.