Faculty Positions
We are recruiting our founding cohort of 7 faculty members across six research tracks, launching January 2027. Click any track to view details and apply.
Faculty Tracks
Position Details
Lead the development of next-generation ultra-low-power sensing systems that actively communicate their own reliability, measurement accuracy, and operational limitations. This faculty position focuses on designing embedded systems architecture, power optimization techniques, and self-characterizing sensor platforms that can adapt to changing environmental conditions. Research will span hardware design, firmware development, and validation of systems deployed in resource-constrained environments.
Research Focus Areas
- Ultra-low-power circuit design and energy harvesting for autonomous sensor networks
- Self-characterizing and self-calibrating sensor systems that report measurement uncertainty
- Real-time signal processing on resource-constrained microcontrollers and edge devices
- Wireless communication protocols optimized for battery-free and minimal-power operation
- Hardware-software co-design for efficient sensor data acquisition and processing
- Validation methodologies for long-term reliability in harsh operational environments
Responsibilities
- Develop and lead an externally-funded research program with publications in top-tier venues
- Teach graduate and undergraduate courses in embedded systems, circuit design, and sensor technology
- Mentor PhD and Master's students; guide hardware prototyping and validation efforts
- Collaborate with other faculty to integrate sensing capabilities across V-SENSE research tracks
- Contribute to institute governance, lab management, and professional community engagement
Required Qualifications
- PhD in Electrical Engineering, Computer Engineering, or closely related field
- Demonstrated expertise in embedded systems design, microcontroller firmware, or sensor hardware
- Strong publication record in peer-reviewed venues (e.g., IEEE, ACM, technical conferences)
- Proven ability to lead independent research and manage research teams
- Experience with circuit design, PCB layout, or microelectronics manufacturing
Preferred Experience
- Hardware prototyping, testing, and deployment in real operational environments
- CMOS design, mixed-signal circuits, or analog front-end development
- Energy harvesting, power management, or battery technology research
- Real-world deployment experience (IoT, wearables, industrial sensors)
- Teaching or mentoring experience; communication with diverse stakeholder groups
Position Details
Pioneer advanced sensing solutions for smart buildings, environmental monitoring, and ambient intelligence systems. This faculty position will drive research into novel sensor modalities and signal processing techniques for occupancy detection, air quality monitoring, thermal imaging, acoustic analysis, and environmental characterization. Work will include developing new sensing approaches, validating systems in real building deployments, and creating frameworks for decision-making in facility management and environmental sustainability.
Research Focus Areas
- Novel sensor modalities for occupancy, thermal comfort, air quality, and environmental monitoring
- Distributed sensor networks for buildings and smart city applications
- Acoustic sensing for activity recognition and speech privacy
- Thermal imaging and infrared sensing for HVAC optimization
- Signal processing and machine learning for environmental data interpretation
- Integration with building management systems and IoT platforms
Responsibilities
- Develop and lead an externally-funded research program with focus on real-world deployments
- Teach graduate and undergraduate courses in environmental sensing, signal processing, and IoT systems
- Mentor graduate students; coordinate field studies and building deployments
- Build partnerships with facility managers, building operators, and industry collaborators
- Publish research findings and present at top-tier conferences in sensing and sustainability
Required Qualifications
- PhD in Environmental Engineering, Building Science, Electrical Engineering, or related field
- Research expertise in environmental monitoring, IoT systems, or sensor networks
- Strong publication record demonstrating thought leadership in the field
- Demonstrated ability to design, build, and deploy sensing systems
- Experience working with building systems, HVAC, or facility management concepts
Preferred Experience
- Deployments in actual buildings or outdoor environments with performance validation
- Signal processing, digital filtering, or spectral analysis expertise
- Experience with building automation systems, BACnet, or facility management protocols
- Partnerships with facility operators, building owners, or sustainability consultants
- Cross-disciplinary collaboration (architecture, mechanical engineering, sustainability)
Position Details
Develop wearable and ambient sensing systems for clinical applications and rehabilitation medicine. This position focuses on designing sensors and algorithms that produce clinically meaningful biomarkers, conducting rigorous validation studies in clinical settings, and translating sensing technology into therapeutic and diagnostic tools. Research will integrate hardware development, signal processing, biostatistics, and clinical collaboration to advance precision medicine.
Research Focus Areas
- Wearable sensors for motion, cardiac activity, respiration, and neurological signals
- Ambient sensors for activity monitoring in rehabilitation and clinical settings
- Biomarker discovery and validation through signal processing and machine learning
- Clinical validation protocols and regulatory pathways for medical devices
- Integration of sensor data with electronic health records (EHR) systems
- Remote patient monitoring and telehealth applications
Responsibilities
- Develop and lead an externally-funded research program with publications in clinical and engineering venues
- Teach graduate courses in biomedical signal processing, medical device design, and clinical validation
- Mentor PhD students and postdoctoral researchers in sensor development and clinical studies
- Establish and maintain collaborations with clinical partners, hospitals, and rehabilitation centers
- Oversee clinical trial design, IRB submissions, and regulatory compliance
Required Qualifications
- PhD in Biomedical Engineering, Clinical Engineering, Biophysics, or related field
- Strong expertise in biomedical signal processing, statistical analysis, or algorithm development
- Experience designing and validating wearable or medical sensors
- Publication record in medical device research, clinical engineering, or biomedical sensing
- Understanding of clinical validation protocols and FDA/regulatory pathways
Preferred Experience
- Clinical trial design, IRB experience, and regulatory submission (510k, PMA) preparation
- Collaboration with clinicians, physicians, and rehabilitation specialists
- Wearable technology development and long-term reliability studies
- Statistical analysis of sensor measurements and biomarker validation
- Commercial medical device or healthcare technology experience
Position Details
Shape how sensing technology meets human and organizational needs responsibly. This faculty position leads research at the intersection of technology, society, and organizational implementation. Focus areas include understanding technology adoption barriers, designing for privacy and ethics, researching implementation in complex organizations, and ensuring sensing systems serve human purposes. This role bridges technical and social science methodologies.
Research Focus Areas
- Human-computer interaction (HCI) for sensor systems and data visualization
- Implementation science and organizational change management for new technologies
- Privacy, ethics, and responsible AI in sensing applications
- User research, qualitative studies, and empirical evaluation in real organizations
- Equity, accessibility, and inclusive design for sensing systems
- Policy implications and regulatory considerations for sensing technology
Responsibilities
- Develop and lead an externally-funded research program combining technical and social science methods
- Teach graduate and undergraduate courses in implementation science, HCI, and responsible technology
- Mentor PhD students in qualitative and mixed-methods research design
- Conduct empirical studies in real organizations, hospitals, schools, or communities
- Bridge collaboration between V-SENSE technical researchers and external stakeholders
Required Qualifications
- PhD in Human-Computer Interaction, Implementation Science, Science & Technology Studies, Ethics, or related field
- Research expertise in technology adoption, organizational behavior, or social aspects of technology
- Strong publication record in peer-reviewed venues
- Demonstrated ability to lead interdisciplinary and cross-functional research
- Expertise in qualitative, quantitative, or mixed-methods research design
Preferred Experience
- Empirical studies in real organizations, institutions, or communities
- Research on privacy, data ethics, or algorithmic fairness
- Collaboration with policymakers, industry practitioners, or community organizations
- Both qualitative (ethnography, interviews) and quantitative methods
- User research and participatory design with diverse stakeholder groups
Position Details
Pioneer novel sensing modalities at the biology-electronics interface. This faculty position drives research into biosensors, implantable systems, chemical detection platforms, and diagnostic devices. Work encompasses novel materials development, electrochemical sensing, optical biosensing, and translation toward validated clinical or commercial applications. Research will require strong collaboration with biologists and chemists to advance the frontier of bioelectronics.
Research Focus Areas
- Novel biosensor designs and bioelectronics architectures
- Implantable sensors for long-term physiological monitoring
- Electrochemical and optical sensing modalities for biomarker detection
- Materials science and interface engineering for biocompatibility
- Microfluidic platforms for point-of-care diagnostics
- Wearable biosensors for non-invasive health monitoring
Responsibilities
- Develop and lead an externally-funded research program with focus on novel sensor platforms
- Teach graduate and undergraduate courses in bioelectronics, materials science, and device design
- Mentor PhD and Master's students in sensor development and device validation
- Collaborate with biologists, chemists, and clinical partners
- Guide transition of laboratory prototypes toward validated devices or commercial products
Required Qualifications
- PhD in Biomedical Engineering, Materials Science, Chemistry, or related field
- Expertise in biosensor design, electrochemistry, optical sensing, or bioelectronics
- Strong publication record demonstrating innovation in novel sensing platforms
- Experience with materials characterization and device validation
- Demonstrated ability to design and prototype sensing devices
Preferred Experience
- Implantable or wearable biosensor development with biocompatibility testing
- Electrochemical sensing, amperometry, voltammetry, or impedance spectroscopy
- Collaboration with biologists, clinicians, or industry partners
- Transition of research prototypes to validated devices or technology licensing
- Familiarity with FDA regulatory pathways and medical device standards
Position Details
Develop algorithms and systems that reason about reliability in sensor data and real-world systems. This faculty position focuses on edge AI, sensor fusion, uncertainty quantification, and trustworthy data pipelines. Research will advance how machine learning systems can acknowledge uncertainty, maintain privacy, process data efficiently on edge devices, and integrate diverse sensor streams in production environments.
Research Focus Areas
- Edge computing and on-device machine learning for resource-constrained systems
- Uncertainty quantification and calibration in neural networks
- Multi-sensor fusion and data integration from heterogeneous sources
- Federated learning and privacy-preserving machine learning
- Trustworthy AI, explainability, and robustness in real-world deployments
- Secure computation and data infrastructure for sensitive applications
Responsibilities
- Develop and lead an externally-funded research program focused on trustworthy AI systems
- Teach graduate courses in machine learning, edge computing, and data systems
- Mentor PhD students in algorithm development and real-world system validation
- Collaborate with V-SENSE domain experts to integrate AI/ML into sensor systems
- Publish research in top-tier ML/AI venues and at application-focused conferences
Required Qualifications
- PhD in Computer Science, Electrical Engineering, Statistics, or related field
- Strong expertise in machine learning, deep learning, or AI systems
- Track record of publications in top-tier ML/AI venues (NeurIPS, ICML, ICCV, JMLR, etc.)
- Experience deploying machine learning systems in real-world or production environments
- Demonstrated understanding of computational efficiency and edge computing constraints
Preferred Experience
- Edge computing, TinyML, or model compression for resource-constrained devices
- Uncertainty quantification, Bayesian methods, or probabilistic inference
- Federated learning, differential privacy, or secure multi-party computation
- Sensor fusion, time series analysis, or multimodal learning from real systems
- Deployment of ML systems with production monitoring and failure analysis
What We Offer
- Research funding for your lab, equipment, and team members
- Operational access to real facilities where your systems are deployed
- Collaborative environment across faculty and industry partners
- Graduate mentorship with full autonomy over your research direction
- Competitive salary and benefits aligned with international standards