Doctoral Research Fellow (BRAINET MSCA DN)

The Unconventional Communications and Computing Laboratory (UC2) at the University of Essex is recruiting Doctoral Research Fellows to undertake PhD projects within BRAINET (Networked Distributed Neural Interfaces for Interference-Based Brain Stimulation), an MSCA Doctoral Network. BRAINET addresses a practical bottleneck in neuromodulation: maintaining the therapeutic value associated with Deep Brain Stimulation while reducing dependence on chronic, deeply implanted hardware by advancing distributed neural interface concepts and safer, more scalable power and information transfer pathways under strict biophysical and safety constraints.

At Essex, the doctoral researchers will be embedded in an engineering-led environment spanning intra-body communications, ultra-low-power biointerfaces, signal processing, and modelling of biophysical channels relevant to neural implants and networked stimulation. The post holders will work as part of a multi-partner European consortium, contributing to defined deliverables and publications, and participating in the network’s structured training and mobility programme, including planned secondments with internationally recognised partners. All work will be carried out in line with University policies on research integrity, ethics and governance, and data management.

DC4 (University of Essex) will develop multiphysical communications for networked power and information transfer to overcome biophysical limitations imposed by the human head. The project will investigate the feasibility of magnetoelectric, near-field communication (NFC), ionic media, and optical modalities; characterise head-related constraints that limit reliable transfer; and develop an optimised multiphysical communication system tailored to those constraints. Expected outcomes include:

• a demonstration of feasibility across the four modalities supporting BRAINET;
• a comprehensive characterisation of human head biophysical limitations relevant to these channels;
• an optimised system design that integrates these constraints to support.

The DC4 researcher will undertake a three-month secondment at Aalborg University (M12) to understand pre-clinical requirements for implantable multiphysics, and a three-month secondment at INRIA (M18), hosted by Dr Malcolm Egan, to integrate robust models of information and power transfer into distributed multiphysical channels.

Ability and willingness to engage in knowledge exchange and outreach activities. Ability and willingness to complement and enhance the research project, department, and school’s education and research strengths, including areas of planned development. Strong written and verbal communication skills. Appreciation of the value of appropriate technologies in research, with the ability and/or willingness to deploy them when relevant. Ability to design and execute rigorous computational experiments, including simulation studies, sensitivity analyses, and benchmarking, and to interpret results against clearly defined performance metrics. Ability to implement, test, and document signal processing and/or communication system components in code, including modulation/coding, channel modelling, and data compression, producing reproducible outputs suitable for publication and consortium use. Ability to work effectively in a multidisciplinary, multi-partner consortium environment, including remote collaboration, structured reporting, and delivery to agreed milestones, including during international secondments. Familiarity with optimisation methods relevant to system design under constraints, including bandwidth limits, energy limits, and safety constraints, or strong evidence of the ability to learn these rapidly.

Specific Requirements: A good honours degree, normally 2:1 or above, in Electrical/Electronic Engineering, Computer Science, Biomedical Engineering, Communications Engineering, Signal Processing, Physics, Mathematics, or a closely related discipline, with eligibility to register for a PhD at the University of Essex. The candidate must not already hold a doctoral-level degree, as this is a grant stipulation. A Master’s degree in Electrical/Electronic Engineering, Computer Science, Biomedical Engineering, Communications Engineering, Signal Processing, Physics, Mathematics, or a closely related discipline.