Biomedical Digital Twin SME
Pivot Path Solutions is building an interdisciplinary team to support advanced research initiatives focused on next-generation biomedical digital twins, predictive physiology, artificial intelligence, and computational modeling of human health and performance. We are seeking a Biomedical Digital Twin Consultant to provide scientific and technical leadership in the development of physics-informed and AI-enabled digital twins capable of simulating human physiological responses under critical medical conditions, including trauma, hemorrhagic shock, cardiovascular instability, and intensive care scenarios. The consultant will work alongside academic researchers, clinicians, data scientists, and software engineers to help advance innovative solutions that combine mechanistic modeling, machine learning, and multimodal healthcare data into actionable decision-support capabilities. This is a remote position; however, candidates located in the Washington, D.C. metropolitan area are strongly preferred.
Key Responsibilities
Provide subject matter expertise in biomedical digital twins, computational physiology, and predictive health modeling. Advise on the development of patient-specific and population-based physiological digital twins. Support the design and validation of models simulating cardiovascular, respiratory, neurological, and metabolic systems. Guide integration of mechanistic models with machine learning and artificial intelligence techniques. Assist in leveraging large-scale healthcare datasets, including ICU, trauma, and longitudinal patient records. Evaluate approaches for real-time prediction of patient deterioration and treatment response. Support model verification, validation, uncertainty quantification, and clinical applicability assessments. Collaborate with clinicians, researchers, and software engineers to translate scientific concepts into operational solutions. Contribute to technical reports, research publications, white papers, and government proposal efforts. Provide strategic guidance on emerging technologies related to digital twins, computational medicine, and AI-driven healthcare. Experience facilitating collaboration among clinicians, researchers, engineers, data scientists, and program sponsors. Skilled in translating complex technical concepts into clear, actionable information for executive leadership, program managers, and non-technical audiences. Desired Technical Expertise Candidates should possess expertise in several of the following areas: Biomedical Modeling Computational physiology Systems biology Physiological simulation Cardiovascular modeling Hemodynamic modeling Respiratory system modeling Trauma and critical care research Hemorrhagic shock modeling Artificial Intelligence & Analytics Machine learning Deep learning Physics-informed machine learning Explainable AI Reinforcement learning Predictive analytics Time-series forecasting Data Science Electronic health records (EHR) ICU and trauma datasets MIMIC-IV Clinical data integration Multimodal healthcare data fusion Signal processing Wearable sensor data Modeling & Simulation Tools MATLAB/Simulink Python Julia R AnyLogic Modelica Digital engineering environments High-performance computing platforms
Required Qualifications
PhD, MD, MD/PhD, or equivalent advanced degree in Biomedical Engineering, Systems Engineering, Computational Biology, Physiology, Applied Mathematics, Data Science, Computer Science, or a related discipline. Minimum 10 years of experience in biomedical research, computational modeling, digital health, or related scientific fields. Demonstrated experience developing or applying physiological, biomedical, or healthcare-focused simulation models. Strong publication record or history of research leadership in relevant disciplines. Experience working with multidisciplinary teams of clinicians, engineers, and researchers.
Preferred Qualifications
Experience supporting DARPA, NIH, DoD, BARDA, ARPA-H, NSF, or federally funded research programs. Experience with digital twin technologies in healthcare or life sciences. Familiarity with trauma medicine, critical care, emergency medicine, or military health systems. Experience developing predictive models for patient outcomes or treatment optimization. Active collaborations with academic medical centers, research institutions, or federal laboratories.