PhD and MS Positions in Hardware-Software Co-Design for Efficient Deep Learning at Case Western Reserve University Case Western Reserve University in United States

Case Western Reserve University is offering PhD, MS, and intern positions in the research group of Prof. Gourav Datta, Assistant Professor in the ECSE Department. The group focuses on hardware-software co-design for efficient deep learning, developing energy-efficient computer vision and multimodal deep learning systems for next-generation intelligent sensing applications. Research areas include smart healthcare, robotics, real-time decision-making at the edge, and embedded systems.

Key research thrusts involve designing autonomous multimodal agents, backpropagation-free learning, memory-augmented and neurosymbolic architectures, deployment of deep learning models on embedded and resource-constrained edge devices (FPGA, microcontrollers), and next-generation computing paradigms such as in-sensor processing and neuromorphic hardware.

Applicants should have strong programming experience in PyTorch/TensorFlow, hardware design experience (HLS/Verilog), Python proficiency, and ideally ML compiler or model deployment experience. Candidates must be self-motivated, possess research curiosity, strong problem-solving abilities in coding and mathematics, and excellent communication skills. Attach a CV, academic transcripts, and a cover letter detailing motivation and relevant experience in ML/hardware.

Funding is fully available for PhD students and exceptional MS students/interns with strong research experience. A $5,000 joining bonus is offered, along with access to extensive computing and lab resources. The lab provides comprehensive mentorship, a collaborative and inclusive environment, and support for publication and experimentation.

To apply, email Prof. Gourav Datta ([email protected]) with the subject line 'Applying to Work on ML HW-SW Co-design', specify desired position (PhD/MS/intern), and attach your CV, academic transcripts, and a cover letter detailing motivation and relevant experience. The application window is open for Spring 2026 and Fall 2026.