Applied AI and clinical data methodology for health and life sciences consortia: study design, statistics, data governance, evidence generation

We are an Istanbul-based medtech SME combining biomedical engineering, applied machine learning and clinical research experience, with peer-reviewed publications and a clinical-grade product developed under IEC 62304-aligned practices. We join consortia with these competencies; the scope is health and life sciences broadly, not limited to medical devices.

What we contribute:

• AI/ML methodology: model evaluation and benchmarking, robustness and degradation analysis, explainability (attention/heat maps), on-device and cloud deployment know-how

• Study design and biostatistics: protocols, sample size, reliability analysis (ICC), equivalence testing, pre-registered analysis plans and their execution

• Clinical data: curation, annotation protocols, anonymization and pseudonymization at source, GDPR/KVKK-compliant data governance across centers

• Evidence and documentation: CLAIM/TRIPOD+AI compliant reporting, regulatory-aware technical documentation (EU MDR, TITCK), QMS-aligned development records

• Open science: pre-registration, code and model release practices, peer-reviewed publication support

What we are looking for:

• Methodology, validation or data-governance partner roles, or a work package lead, in Horizon Europe and Eurostars projects: digital health, medical AI, clinical research infrastructure, life sciences data projects

• As a Turkish SME, we bring our own national funding channel (TUBITAK) into Eurostars and Horizon projects, reducing the budget burden on other partners

Languages: English, Turkish. Remote-first, EU-timezone friendly.