Senior Research Officer, School of Computer Science and Electronic Engineering

University of Essex
Colchester
2 years ago
Applications closed

Related Jobs

View all jobs

Senior Data Research Engineer Computer Vision

Senior Data Scientist Research Engineer

Senior Data Scientist Research Engineer

Senior Data Scientist

Senior Genomic Data Scientist - 2 Year FTC, Adult Population Genomics Programme (we have office locations in Cambridge, Leeds & London)

Senior Data Scientist

The School of Computer Science and Electronic Engineering (CSEE)

The School of Computer Science and Electronic Engineering (CSEE) is a large and dynamic department in the Faculty of Science and Health. The School is internationally known for its research in a range of areas and offers an excellent education to its students.

The Brain-Computer Interfaces and Neural Engineering (BCI-NE) laboratory

CSEE hosts the BCI-NE lab that was founded in 2004 and is today one of the largest and best equipped in Europe and the top laboratory for non-invasive BCIs and human cognitive augmentation in the UK. For two decades, the lab has produced highly visible internationally leading research, peer reviewed publications and frequent media presence, with international (MIT, NASA JPL, ESA, Harvard, UCB) and national (Oxford, Imperial, UCL) collaborations. Indeed, it has been singled out as a world class element of CSEE in recent Research Evaluation Frameworks.

The BCI-NE lab are now seeking two Senior Research Officers on a three-year fixed-term, full time basis, to work on the project ‘Semantic brain to computer communication’.

The Project and Duties of the Role

This project proposes a radically new BCI based on semantic decoding: directly identifying whole concepts an individual is thinking of from a combination of analysis of brain activity and natural language modelling. Specifically, the work will include running a series of experiments to record neural data while individuals focus on a series of individual concepts. This will include experiment design and work on extraction of information from electroencephalogram (EEG), functional near infrared spectroscopy (fNIRS) and other physiological signals. The work will also include analysis work to develop decoding models (including development and evaluation of signal processing and machine learning pipelines), as well as development of natural language models and integration of natural language modelling with neural decoders to develop novel forms of Brain-Computer Interface. The project will involve working with the project team to explore how neural engineering technology can be used to provide accurate, real-time, decoding of user intention.

The successful applicant will work on these duties, on a day-to-day basis within the BCI-NE lab.

A full list of duties can be found within the respective job packs.

Skills and Qualifications Required
Applicants are expected to hold a PhD (or be very close to submitting their PhD thesis) in Biomedical Engineering, Brain-Computer Interfaces, Neural Engineering, Electronic Engineering, Statistics, Physics, Computer Science, Neuroscience or a closely related discipline. You will be expected to have evidence of a developing research agenda and a developing record of publications in internationally recognised, reputable journals.

The successful candidate will have significant experience in programming and will ideally also have experience in areas such as signal processing, machine learning, statistical modelling of neural signals and processes, ), along with strong communication skills.

Applicants are also expected to have a strong publication record (relative to their career stage) as first author, ideally including publications in 1st quartile journals in relevant areas.

At the University of Essex, internationalism and diversity is central to who we are and what we do. We are committed to being a cosmopolitan, internationally oriented university that is welcoming to staff and students from all countries, faiths and backgrounds, where you can find the world in one place.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.