A compact and low-noise analog front-end for neural recording applications

One method of studying and treating neurological conditions is through the use of neural implants. These devices interface directly with neural tissue and enable the recording and modulation of brain activity. A key component of such systems is the neural recording front-end, which converts small bioelectrical signals into digital data for further processing. This front-end typically includes an analog-to-digital converter (ADC) capable of measuring the surrounding electrical potential. In particular, recording the local field potential (LFP) is of significant interest, as it enables applications such as closed-loop neurostimulation and neural decoding of movement. As neural implants operate under strict constraints on size, power, and signal quality, achieving low input-referred noise (<2 μVrms) and a compact area footprint is essential. The objective of this thesis is to design such a neural readout circuit through (1) an exploration of the current state of the art and relevant literature, (2) system- and circuit-level design, and (3) verification. Type of internship : Master internship Duration : 6-12 months Required educational background : Electrotechnics/Electrical Engineering, Biomedical engineering University promotor : Georges Gielen (KU Leuven) Supervising scientist(s) : For further information or for application, please contact Hsukang Chen ( Hsukang.Chen@imec.be ) The reference code for this position is 2026-INT-150 . Mention this reference code in your application. Only for self-supporting students. Applications should include the following information: resume motivation current study Incomplete applications will not be considered