Researcher – Postdoctoral Researcher

Postdoctoral Researcher – Biophysics‑Informed Digital Twins in Clinical Trials IE University’s Health & Data Lab invites a postdoctoral researcher to develop biophysics‑informed neural networks (BioPINNs) that combine physiological and pharmacokinetic knowledge with deep learning to build digital twins of patients for simulating treatment responses in silico. Project Overview Build a unified BioPINN framework merging mechanistic models with Universal Differential Equations and Neural ODEs. Learn individualized latent states describing patient physiology before and after treatment. Generate digital twins to perform counterfactual simulations (“what if” scenarios) informing trial design and patient stratification. Validate models using simulated data and real‑world datasets. Responsibilities Lead development and evaluation of advanced AI models to understand patient trajectories and treatment response. Contribute to the design of digital twin and counterfactual simulation frameworks to support decision‑making in clinical trials. Drive scientific dissemination through publications, presentations, and open‑source software. Support grant‑writing efforts and help shape the future direction of the project and related collaborations. Mentor students or junior researchers and foster a collaborative, open research culture within the Health & MedTech Lab. Qualifications PhD (completed or near completion) in Computer Science, Applied Mathematics, Statistics, Physics, Engineering, Biomedical Engineering, Computational Biology, or a related field. Strong background in machine learning / deep learning, with experience in: Time‑series modeling, sequence models, or longitudinal data Differential equation‑based models (Neural ODEs, PINNs, UDEs) Probabilistic modeling, Bayesian methods, or uncertainty quantification Excellent Python programming skills and experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow. Demonstrated research track record (publications, preprints, or strong thesis) in machine learning, computational modeling, or related fields. Experience working with real‑world data (preferably health/clinical or biomedical datasets) and comfortable with data wrangling, preprocessing, and exploratory analysis. Strong analytical and problem‑solving skills, and ability to work independently and as part of a multidisciplinary team. Fluency in English (Spanish not required). Highly valued (but not mandatory) Experience with causal inference, counterfactual modeling, or treatment‑effect estimation. Familiarity with pharmacokinetic or physiological modeling. Experience with software engineering best practices. Experience in interdisciplinary collaborations involving clinicians, biologists, or industry partners. What We Offer Full‑time postdoctoral position (12 months) based in Madrid (IE Tower), within the Health & MedTech Lab. Opportunity to build collaborations with top‑tier academic and industry partners. Work on high‑impact problems at the interface of AI, biophysics, and clinical research, with tangible applications to clinical trials and patient care. Access to a modern computational environment (high‑end workstation, HPC resources as available). Support for travel and dissemination (conferences, workshops, partner visits). Stimulating, international, and entrepreneurial environment within IE University, with opportunities to contribute to teaching, mentoring, and innovation activities if desired. Equal Opportunities IE University actively promotes equal opportunities in recruitment and access to employment. We ensure the absence of bias based on gender, sexual orientation, religion, age, ethnic origin, or disability throughout the entire selection process. #J-18808-Ljbffr