Desired Expertise for Technical SETA - Systems Biology and Compu

Job Title: Desired Expertise for Technical SETA - Systems Biology and Computational Modeling

Clearance: Public Trust Required upon application

Location: Washington D.C./Hybrid

Education: Advanced degree (Ph.D. preferred) in systems biology, computational biology, or a related field with a focus on medical applications

The ideal candidate for this Systems Engineering and Technical Assistance (SETA) position will possess advanced expertise in systems biology and computational modeling, complemented by deep medical and clinical knowledge. This role requires a unique blend of technical, interdisciplinary, and regulatory skills to guide the development of innovative digital health solutions, leveraging AI and digital twin technologies to improve patient care and outcomes.

Key Qualifications

1. Systems Biology and Computational Modeling:
• Advanced degree (Ph.D. preferred) in systems biology, computational biology, or a related field with a focus on medical applications.
• Extensive experience modeling complex biological systems, encompassing multi-scale processes from molecular to physiological levels.
• Demonstrated expertise in developing and validating multiscale biological models, particularly for human physiology and disease processes.
• Proven ability to integrate multi-omics datasets (genomics, proteomics, metabolomics) into actionable biological simulations.
• Proficiency in modeling techniques such as ordinary differential equations, agent-based modeling, and network analysis tailored to biological systems.
2. Medical and Clinical Expertise:
• Strong foundation in human anatomy, physiology, and pathology, with emphasis on conditions requiring personalized, proactive, and continuous management.
• Practical experience working with diverse clinical datasets, including EHRs, medical imaging, and real-time health monitoring data streams.
• Familiarity with current trends in digital twin technologies for healthcare, especially in personalized medicine and clinical decision support.
3. Innovation in Digital Health and AI Integration:
• Insight into healthcare challenges, patient care workflows, and regulatory and ethical considerations in digital health.
• Expertise in leveraging AI for applications such as remote monitoring, disease trajectory forecasting, and adaptive treatment strategies using personalized digital twins.
• Comprehensive knowledge of the challenges and emerging opportunities in implementing digital twin technologies for healthcare.
4. Collaborative and Interdisciplinary Skills:
• Track record of successful collaboration with clinicians, biologists, data scientists, and engineers to achieve interdisciplinary program goals.
• Ability to bridge the gap between biological systems and computational modeling to ensure accurate and clinically meaningful digital twin representations.
5. Regulatory and Ethical Considerations:
• Knowledge of regulatory frameworks for healthcare technology development and clinical trials.
• Awareness of data privacy, security, and ethical concerns in using personal health data within digital twin applications.

Prior Experience Requirements:

• Excellent organizational and communication skills, strong attention to detail, and the ability to handle a wide variety of tasks, including briefing support and general administration.
• Strong technical writing skills with an ability to prepare effective documentation.
• Highly organized, self-motivated, detail-oriented, and adept at multitasking in a high-pressure environment. Demonstrated ability to respond quickly and manage changing priorities effectively.
• Advanced degree (Ph.D. preferred) in systems biology, computational biology, or a related field with a focus on medical applications.
• 4+ years of experience in project management, research management, grants management, or related fields.

Additional Preferred Experience:

• Experience supporting human subjects research and animal research, including regulatory management and oversight.
• Experience in mixed-methods quantitative and qualitative data collection, analysis, interpretation, and dissemination.
• Experience developing Standard Operating Procedures (SOPs) for research programs.
• Government experience with extramural R&D funding.
• Prior experience in supporting leadership

Summary

The ideal candidate will have a proven ability to integrate complex biological and clinical data with advanced computational techniques. They will be instrumental in driving innovations in digital twin technology, ensuring alignment with clinical needs and regulatory standards to enable transformative advancements in personalized healthcare.