Research Assistant / Associate

Research Assistant / Associate

Full-Time 43863 - 57472 € / year (est.) No home office possible
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At a Glance

  • Tasks: Develop next-gen sensing tech for sleep and physiological monitoring.
  • Company: Join a world-leading institution at Imperial College London.
  • Benefits: Competitive salary, collaborative environment, and opportunities for research publication.
  • Other info: Full-time role with excellent career development and collaboration opportunities.
  • Why this job: Make a real-world impact in health monitoring and dementia care technologies.
  • Qualifications: PhD in relevant fields and experience in signal processing or machine learning.

The predicted salary is between 43863 - 57472 € per year.

Job number: ENG03929

Salary range: Β£43,863- Β£57,472 per annum

Location: South Kensington Campus - On site only

Contract type: Full time - Fixed term

Posting End Date: 4 Jun 2026

About the role:

Are you interested in developing next-generation sensing technologies for unobtrusive sleep and physiological monitoring? In this role, you will contribute to research that uses radar and complementary sensing technologies to monitor sleep and related physiological signals in living-lab and home-like environments. You will work as part of a multidisciplinary team developing algorithms, experimental methods and research prototypes that could support future technologies for dementia care, sleep health and long-term remote monitoring.

What you would be doing:

  • Develop and evaluate signal processing and machine learning methods for interpreting radar and multimodal physiological data.
  • Focus on extracting meaningful sleep and physiological information from unobtrusive sensing systems, including respiration, cardiac activity, body movement, sleep posture and sleep-related events.
  • Help design and run validation studies with human participants, including the collection and analysis of data from radar, sleep monitoring systems and reference physiological measurements.
  • Contribute to the development and refinement of research prototypes, including radar systems, under-mattress or contactless sensing devices, and associated data acquisition pipelines.

What we are looking for:

  • A motivated and collaborative researcher with experience in one or more of the following areas:
  • A PhD in Electronic Engineering, Biomedical Engineering or Computer Science.
  • Experience in signal processing and machine learning for physiological, biomedical, radar, wearable, contactless or multimodal sensor data.
  • Experience with radar systems.
  • Strong programming skills, for example in MATLAB, Python or equivalent tools.
  • An interest in sleep monitoring, remote sensing, dementia care technologies or long-term health monitoring.
  • Excellent written and communication skills.
  • Ability to work independently, manage competing deadlines and collaborate effectively.

What we can offer you:

  • The opportunity to continue your research career at a world-leading institution.
  • The opportunity to work within a collaborative and multidisciplinary research environment.
  • The opportunity to contribute to research with real-world translational potential.
  • Access to expertise and collaborations across Imperial College London, the UK Dementia Research Institute Care Research & Technology Centre, the University of Surrey and wider academic and clinical networks.
  • Opportunities to publish in high-quality journals, present at national and international conferences, and contribute to grant proposals and future research directions.
  • Opportunities to develop skills in radar sensing, physiological signal analysis, experimental design, machine learning, and prototype development.

Further information:

This is a full-time post. This role is for a fixed-term contract for 12 months. The post will be based in the Department of Electrical and Electronic Engineering at Imperial College London, within the Bioelectronics Group and the Next Generation Neural Interfaces Lab. The postholder will work closely with collaborators in the UK Dementia Research Institute Care Research & Technology Centre and related research partners. Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.

Research Assistant / Associate employer: SONICOM

Imperial College London is an exceptional employer, offering a vibrant and collaborative work culture that fosters innovation in research. As a Research Assistant/Associate, you will have the unique opportunity to contribute to groundbreaking projects in sleep monitoring and dementia care, while benefiting from access to world-class expertise and resources. With a focus on employee growth, you will be encouraged to publish your findings, present at prestigious conferences, and develop valuable skills in a supportive environment located in the heart of South Kensington.

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Contact Detail:

SONICOM Recruiting Team

StudySmarter Expert Advice🀫

We think this is how you could land Research Assistant / Associate

✨Tip Number 1

Network like a pro! Reach out to people in your field, attend relevant events, and connect with researchers at institutions like Imperial College London. You never know who might have the inside scoop on job openings or can put in a good word for you.

✨Tip Number 2

Show off your skills! Prepare a portfolio or a presentation that highlights your projects, especially those related to signal processing and machine learning. This will give you an edge during interviews and show that you're ready to contribute from day one.

✨Tip Number 3

Practice makes perfect! Conduct mock interviews with friends or mentors to refine your responses, especially around your experience with radar systems and physiological data. The more comfortable you are, the better you'll perform when it counts.

✨Tip Number 4

Apply through our website! We love seeing candidates who take the initiative. Make sure to tailor your application to highlight your interest in sleep monitoring and dementia care technologies, as this will resonate with what we're looking for.

We think you need these skills to ace Research Assistant / Associate

Signal Processing
Machine Learning
Radar Systems
Programming Skills
MATLAB
Python
Data Analysis

Some tips for your application 🫑

Tailor Your CV:Make sure your CV is tailored to the role of Research Assistant/Associate. Highlight your experience in signal processing, machine learning, and any relevant projects that showcase your skills in radar systems and physiological data analysis.

Craft a Compelling Cover Letter:Your cover letter should tell us why you're passionate about sleep monitoring and dementia care technologies. Share specific examples of your work and how it aligns with our research goals. Keep it engaging and personal!

Showcase Your Skills:Don’t forget to mention your programming skills! Whether it's MATLAB, Python, or other tools, let us know how you've used these in your previous projects. This will help us see how you can contribute to our multidisciplinary team.

Apply Through Our Website:We encourage you to apply through our website for a smooth application process. It’s the best way to ensure your application gets to the right people and stands out in our system!

How to prepare for a job interview at SONICOM

✨Know Your Stuff

Make sure you brush up on your knowledge of signal processing and machine learning, especially as it relates to physiological data. Be ready to discuss your previous projects and how they align with the research focus of the role.

✨Show Your Passion

Express your genuine interest in sleep monitoring and dementia care technologies. Share any personal experiences or motivations that drive your passion for this field, as it can really resonate with the interviewers.

✨Prepare for Technical Questions

Expect some technical questions about radar systems and programming skills. Practise explaining complex concepts in simple terms, as this will demonstrate your understanding and communication skills.

✨Collaborative Mindset

Highlight your ability to work in a multidisciplinary team. Prepare examples of past collaborations and how you contributed to achieving common goals, as teamwork is key in this role.