Postdoctoral Fellow - Analog/Mixed-Signal ASIC Design and Embedded TinyML

Researcher Profile: First Stage Researcher (R1) Positions: Postdoc Positions Application Deadline: 25 Dec 2026 - 23:00 (America/New_York) Country: Canada Type of Contract: Temporary Job Status: Full-time Hours Per Week: 35 Offer Starting Date: 4 Jan 2027 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description 1. Position title Postdoctoral Fellow - Analog/Mixed-Signal ASIC Design and Embedded TinyML Optical Spinal Implant (OSI) project - analog acquisition, embedded intelligence, and closed-loop control 2. Research environment Join a $5 Million Research Alliance Advancing Next-Generation Neurotechnology Professor Benoit Gosselin’s Smart Biomedical Microsystems Laboratory (sBioML) at Université Laval is recruiting a postdoctoral fellow to join the Optical Spinal Implant (OSI) program, a major $5 million, five-year research initiative funded through the NSERC Alliance Society program . Led by Université Laval, this ambitious multidisciplinary collaboration brings together researchers from four Canadian universities , alongside industrial, clinical, and patient-community partners. Combining world-class expertise in microelectronics, neuroscience, optogenetics, wireless technologies, and preclinical research, OSI aims to advance a new generation of intelligent, implantable neurotechnologies for chronic pain. At the heart of this initiative is the development of a miniaturized, intelligent optical spinal implant integrating cell-specific optogenetic stimulation, fluorescence-based neural sensing, ultra-low-power integrated circuits, embedded AI, and wireless communication. The platform aims to enable precise, adaptive, closed-loop modulation of spinal circuits involved in neuropathic and nociceptive pain. Addressing demanding challenges in miniaturization, energy efficiency, safety, and biocompatibility, the program spans cutting-edge technology development through preclinical validation in small- and large-animal models. The successful candidate will contribute to this large-scale collaborative effort at the intersection of advanced bioelectronics, artificial intelligence, and neuroscience. 3. Position description The successful candidate will play a leading role in the co-design of the OSI's intelligent microelectronic system. The position jointly covers ultra-low-power analog and mixed-signal integrated circuit design and the development and deployment of TinyML models that interpret fluorescence signals and adapt optical stimulation in real time. Mandate and objectives Design and validate the complete signal chain from sensor interface to embedded decision-making. The work will include low-noise analog front ends for photodiodes, signal conditioning and data conversion, stimulation and power-management circuits, and the digital blocks required for processing. In parallel, the candidate will develop, compress, and deploy TinyML models under severe memory, computation, latency, and energy constraints. Hardware-algorithm co-design will jointly optimize signal quality, model accuracy, and implant power consumption. Examples of projects and responsibilities Design, simulate, and verify ultra-low-power analog or mixed-signal ASIC blocks, including photodiode interfaces, low-noise amplifiers, filters, data converters, references, stimulation circuits, and power-management circuits. Develop and evaluate TinyML models for pain-state detection and adaptive control; perform feature selection, quantization, pruning, distillation, and deployment on microcontrollers, FPGAs, or integrated hardware accelerators. Perform hardware-algorithm co-simulation, tape-out, and bench characterization, then integrate the analog chain, TinyML engine, interposer, flexible circuit, LEDs, photodiodes, and UWB link. Depending on project needs, contribute to the evaluation of inductive, capacitive, ultrasonic, or hybrid wireless power transfer (WPT) solutions. Typical week The work will combine analog circuit design and simulation, TinyML model development and optimization, architecture reviews, verification, test-bench development, prototype characterization, data analysis, scientific writing, and mentoring. The fellow will work at the interface of microelectronics, artificial intelligence, neuroscience, RF, and microsystems teams. Where to apply E-mail: osi@gel.ulaval.ca Requirements Research Field: Engineering » Electrical engineering — Education Level: PhD or equivalent Research Field: Engineering » Computer engineering — Education Level: PhD or equivalent Skills/Qualifications We are seeking a versatile, independent, and rigorous researcher who can contribute meaningfully to both core areas of the position: analog/mixed-signal integrated circuit design and embedded artificial intelligence. The scientific challenge is to connect analog-front-end signal quality, computing architecture, and TinyML performance within a highly constrained implant. Essential qualifications PhD in electrical engineering, microelectronics, computer engineering, or a closely related field, completed or near completion by the start date. Demonstrated expertise in analog or mixed-signal CMOS integrated circuit design - including simulation, verification, and ideally silicon characterization - together with experience in machine learning, signal processing, and model deployment on embedded platforms. Strong scientific programming skills and the ability to conduct hardware-algorithm co-design, produce reproducible results, publish research, mentor students, and collaborate within an interdisciplinary team. Specific Requirements Assets (preferred, not required) Experience with a microelectronic CAD environment, particularly Cadence Virtuoso, and an analog or mixed-signal ASIC flow; experience with Python and a machine-learning framework such as PyTorch or TensorFlow, as well as quantization, code-generation, or TinyML deployment tools. Knowledge of low-signal sensor interfaces, data converters, accelerator architectures, biomedical signal processing, bioinstrumentation, optoelectronics, or RF/UWB systems. Experience with inductive, capacitive, ultrasonic, or hybrid wireless power transfer (WPT) is an additional asset but is not required. Languages: ENGLISH — Level: Good Languages: FRENCH — Level: Basic Research Field: Engineering » Electrical engineering; Engineering » Computer engineering Additional Information Work Location(s) Number of offers available: 1 Company/Institute: Smart Biomedical Microsystem Laboratory Country: Canada State/Province: QC City: Québec Postal Code: G1V 0A6 Street: 1065 Av. de la Médecine Contact State/Province: QC City: Québec Website: https://project-osi.ca/ Street: 1065 Av. de la Médecine Postal Code: G1V 0A6