Post-doctoral Fellow in Computational Neuroscience and Neuroengineering

University of Hong Kong Hong Kong, Hong Kong

About the position

Established in 2025, the School of Biomedical Engineering (SBME) at
HKU represents an unprecedented joint-force across the Faculties of
Medicine, Engineering, Dentistry and Science—uniting their strengths in a single vibrant research and education hub. As one of
HKU’s newest academic units, SBME provides an unparalleled platform for interdisciplinary translational research and innovation. This collaborative environment empowers researchers to break new ground at the convergence of biomedicine and engineering, driving transformative breakthroughs that will redefine healthcare both locally and globally.

Applications are invited for appointments as Post-doctoral
Fellow in Computational Neuroscience and Neuroengineering, School of Biomedical Engineering (Two posts) (Ref.: 537846) (to commence as soon as possible on a temporary basis for a one-year or two-year temporary term contract, with the possibility of renewal subject to funding availability and satisfactory performance.

Duties and Responsibilities

  • Conduct cutting-edge research in computational neuroscience and

neuroengineering, with a particular focus on neural data analysis, neural decoding, brain–computer interfaces (BCIs), and
NeuroAI.

  • Develop and apply advanced computational methods, including

machine learning, deep learning, and statistical modeling, to analyze large-scale neural recordings and understand neural dynamics and information processing.

  • Develop novel algorithms for neural signal processing,

decoding, and closed-loop neuromodulation.

  • Investigate fundamental principles of neural computation and

explore their applications in neuroengineering and artificial intelligence.

  • Collaborate with interdisciplinary research teams on projects

involving neural interfaces, electrophysiology, computational modeling, and AI-driven neuroscience.

  • Drive research projects toward defined scientific goals and

publish findings in high-impact academic journals and conferences.

  • Prepare research proposals, scientific manuscripts, reports,

and presentations.

  • Mentor junior researchers and students, and assist with other

research-related activities as assigned by the supervisor.

Requirements

  • A PhD degree in Neuroscience, Biomedical Engineering,

Electrical Engineering, Computer Science, Applied Mathematics,
Physics, or a closely related field.

  • Strong research background in one or more of the following

areas: computational neuroscience, neural data analysis, neural signal processing, neural decoding, brain–computer interfaces, machine learning, or neuroengineering.

  • Proficiency in scientific programming, particularly Python, and

experience with computational frameworks commonly used in neuroscience or machine learning.

  • Experience analyzing electrophysiological recordings, including

single-unit, multi-unit, ECoG, or EEG data, is highly desirable.

  • Experience in deep learning, neural dynamical systems, neural

population modeling, or AI-based neural decoding is an advantage.

  • A strong publication record and demonstrated ability to conduct

independent and innovative research.

  • Excellent written and verbal communication skills in

English.

  • Strong motivation, scientific curiosity, research integrity,

and the ability to work both independently and collaboratively in an interdisciplinary research environment.

A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits.

The University only accepts online application for the above post.
Applicants should apply online at the University’s Careers site and upload an up-to-date C.V. Review of applications will start on
November 20, 2026 and continue until December 31, 2026 , or until the post is filled, whichever is earlier.

Advertised: Nov 10, 2026 (HK Time)

Applications close: Dec 31, 2026 (HK Time)

This listing was collected from a public source and is reproduced here for information only. Always confirm the details on the original posting before applying.
View the original posting

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