At a Glance
- Tasks: Lead innovative research using AI and algorithms on real-world signals and sensor fusion.
- Company: Leading research institution with a focus on cutting-edge technology.
- Benefits: Competitive salary, strong pension, extra holidays, and professional development opportunities.
- Other info: Hybrid working available; great public transport access to the office.
- Why this job: Make a real impact in defence and national security while advancing your career.
- Qualifications: PhD in relevant field and experience in data science and signal processing.
The predicted salary is between 70000 - 90000 £ per year.
R&D applying AI and algorithms to real-world signals/comms, sensor fusion London, hybrid working; to £58k plus benefits. This senior position has a three-year term with a leading research institution and has strong Data Science elements. As a PhD-qualified scientist with further research or commercial experience, you will bring your prior experience in signal processing to bear. You'll be helping to establish and further the state of the art, with a view to paving the way for future technology adoption and new applications. This work does involve collaboration with defence and national security stakeholders. Sole British nationality is required, as is the ability to gain security clearance (with institutional support). The work will focus on radio frequency communications (RF, EME) and the application of state-of-the-art AI techniques. You do not need RF or AI experience (though these are advantageous). You will have the aptitude and interest, and prior experience developing techniques and algorithms for working with analogue signals.
Specifically, you will have:
- A PhD in physics, maths, engineering or a similar field
- Additional experience in research or commercial R&D (including a leading/mentoring role in some capacity, either for a small team, research project, or supervising PhDs, etc.)
- Expertise in data science, analogue signal processing techniques, and algorithm development (whether with RF, radar, wireless comms, audio, SDR or medical devices, etc.), ideally including sensor fusion techniques
- Good Python or equivalent coding skills, happy to contribute to a codebase
- Good technical communication skills and the ability to lead meetings, talks and briefings
- A track record of publication including journal-quality results, employing analysis and visualisation of data
- An interest in mentoring and assisting junior researchers
The role comes with opportunities for collaborative research into a range of new areas, learning and applying new techniques whilst building your reputation through contributions and publications. As well as a competitive salary, good benefits are on offer including a strong pension, additional holidays, and professional development. Offices are easy to reach via public transport, and hybrid working is available.
Senior Research Scientist in Fraserburgh employer: ECM Selection Ltd.
As a leading research institution located in London, we offer an exceptional work environment that fosters innovation and collaboration in the field of AI and signal processing. Our hybrid working model provides flexibility, while our commitment to professional development ensures that you will have ample opportunities for growth and mentorship. With competitive benefits including a strong pension and additional holidays, we are dedicated to supporting our employees both personally and professionally.
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We think you need these skills to ace Senior Research Scientist in Fraserburgh
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
