Postdoctoral Fellow – Artificial Intelligence, Digital Twin Systems, and Biomedical Sensing

Postdoctoral Fellow – Artificial Intelligence and Digital Twin Systems The MooAnalytica Research Group at Dalhousie University invites applications for a Postdoctoral Fellow in Artificial Intelligence and Digital Twin Systems. We seek an exceptional early-career researcher with a strong background in artificial intelligence, machine learning, multimodal sensing, and cyber-physical systems who can contribute to and help lead innovative research at the intersection of intelligent sensing, biomedical signal analysis, and digital twin technologies. The successful candidate will participate in the development of AI-enabled digital twin platforms and multimodal analytics systems for complex biological environments. These systems integrate video, acoustic, physiological, and environmental sensing to support intelligent monitoring, predictive analytics, and real-time decision support in real-world systems. Research within the group spans several AI and sensing domains, including: Artificial Intelligence and Machine Learning Digital Twin Systems and Cyber-Physical Infrastructure Multimodal Sensing and Biomedical Signal Processing Computer Vision and Bioacoustic Analytics Intelligent Monitoring Systems for Biological Environments Edge AI and Sensor Data Fusion Responsibilities The postdoctoral fellow will play a leadership role within the research group and will be expected to: Lead research initiatives in artificial intelligence, machine learning, and digital twin systems Supervise and mentor MSc, PhD, and undergraduate researchers Publish research findings in high-impact journals and international conferences Contribute to the development of course materials and training modules in AI for digital systems, intelligent sensing, cybersecurity, or applied machine learning Assist in coordinating interdisciplinary research projects across collaborating groups Contribute to proposal development and collaborative research initiatives Develop software systems, machine learning pipelines, and research prototypes Required Qualifications Applicants must have: A PhD in Computer Science, Artificial Intelligence, Biomedical Engineering, Electrical Engineering, or a closely related discipline Strong programming expertise in Python and modern machine learning frameworks such as PyTorch or TensorFlow Experience in machine learning, multimodal data analysis, signal processing, or AI system development Demonstrated research productivity through peer-reviewed publications Evidence of research independence, initiative, and leadership potential Preferred Expertise Preference will be given to candidates with experience in one or more of the following areas: Computer vision or video analytics Multimodal machine learning Biomedical signal processing or acoustic analysis Sensor fusion and IoT systems Digital twin systems or cyber-physical systems Edge AI and real-time sensing systems Research Environment The MooAnalytica Research Group develops AI-driven digital twin technologies and intelligent sensing systems for complex biological and environmental systems. The group integrates machine learning, multimodal sensing, computer vision, and data infrastructure to support next-generation intelligent monitoring and decision-support platforms. The postdoctoral fellow will work in a highly interdisciplinary environment spanning artificial intelligence, sensing systems, and applied biological systems, with opportunities to collaborate with academic, industry, and international partners. Career Development We particularly encourage applications from candidates who aspire to academic careers and demonstrate the ability to lead independent research initiatives, mentor junior researchers, and contribute to the development of new interdisciplinary research directions.