Open position for a tenure-track Assistant Professor in the area of digital health https://apply.interfolio.com/117048
Building on more than three decades of research successes, a major goal of our research program is to prove, encourage, and support new and far-reaching initiatives that look 10+ years into the future. Driven by a core group of internationally recognized faculty, extensively and uniquely experienced in research and education, our culture fosters close collaboration, which is the major force that maximizes technology impact and direction. Through various funding programs, Rice has been able to demonstrate leadership in focused research initiatives: Computer Engineering; Data Science; Neuroengineering; Optics and Photonics, Wireless Networking, Sensing and Security, Health, and Quantum Engineering.
The research in this discipline focuses on many different aspects and touches on virtually every area that CE encompasses. Analog and mixed signal design, including self-healing circuits and large-scale radiating integrated circuits for medical imaging. Computer architecture and embedded systems, like those in biosensors and mobile wireless healthcare and parallel computing for data science algorithms, large-scale storage systems, and resource scheduling for performance, power and QoS. Hardware security and storage, such as the security schemes which are being based on physically unclonable functions. VLSI signal processing focuses on algorithms for wireless communication systems and their efficient mapping to low-power architectures on DSPs, GPUs, ASICs, and ASIPs. Last but not least is biosensors and computer vision — smartphones with imaging devices are leading to new areas in computer vision and sensing.
Data Science is an emerging discipline that integrates the foundations, tools and techniques involving data acquisition (sensors and systems), data analytics (machine learning, statistics), data storage and computing infrastructure (GPU/CPU computing, FPGAs, cloud computing, security, and privacy) in order to enable meaningful extraction of actionable information from diverse and potentially massive data sources. Data scientists in ECE use digital signal processing algorithms to collect and understand the structure in data, looking for compelling patterns, telling the story that's buried in the data. They get to the questions at the heart of complex problems and devise creative approaches to making progress in a wide variety of application domains.
The brain is essentially a circuit. Neuroengineering is a discipline that exploits engineering techniques to understand, repair, and manipulate human neural systems and networks. At Rice, we have a world-class team collaborating with Texas Medical Center Researchers to improve the fundamental understanding of coding and computation in the human brain as well as to develop technology for treating and diagnosing neural diseases. Current research areas include interrogating neural circuits at the cellular level, analyzing neuronal data in real-time, and manipulating healthy or diseased neural circuit activity and connectivity using nanoelectronics, optics, and emerging photonics technologies.
Optics and Photonics
The focus of this program is the improved understanding of electronic, photonic, and plasmonic materials, optical physics, the interaction of light and matter, along with the application of that knowledge to develop innovative devices and technologies. The specific areas of interest cover a broad range: Nanophotonics and plasmonics, optical nanosensor and nano-actuator development, studies of new materials, in particular, nanomaterials and magnetically active materials; imaging and image processing, including multispectral imaging and terahertz imaging; ultrafast spectroscopy and dynamics; laser applications in remote and point sensing, especially for trace gas detection; nanometer-scale characterization of surfaces, molecules, and devices; organic semiconductor devices; single-molecule transistors; techniques for optical communications; optical interactions with random, nanoengineered, and periodic media; and applications of Nanoshells in biomedicine.
Wireless Networking, Sensing and Security
Rice researchers are inventing the future of wireless, from theoretical foundations to at-scale field trials. Wireless networking research explores new spectrum, new devices, and new architectures to realize the next generation of functionality and performance. Wireless sensing research fuses advanced communication capabilities with advanced sensing capabilities by analyzing radio-frequency signals to understand the physical world. Wireless security targets to ensure that communication infrastructure is resilient in the presence of adversaries that attempt to intercept or disrupt communications.
The Rice ECE Digital Health research area focuses on research in engineering innovations that could transform future healthcare systems. Specific current and growth areas of interest are: bio-imaging/sensing, medical imaging, multi-omics, personalized health, bio-electronics, wearables and point-of-care devices, signal processing, machine learning, control for health, AR/VR/visualization/information systems for health, and robotics for health. Research in digital health spans the spectrum from early-stage technology development to translational efforts. The faculty collaborate with many clinical partners nationally and have many close collaborations with the Texas Medical Center (TMC), which is the largest medical center in the world.
Quantum mechanics has been studied in the research community for nearly a century, providing rules that explain physical processes in atoms, molecules, and solids, which led to the invention and commercialization of lasers, MRI imagers, transistors, and nuclear power generation. Now the field is undergoing a revolution, enabling even more powerful applications, based on genuinely quantum, nonintuitive concepts such as superposition and entanglement. We are utilizing cutting-edge photonic, electronic, and magnetic technologies to control excitons, phonons, plasmons, magnons, and polaritons in quantum materials for applications in quantum simulation, quantum sensing, and quantum networks.