At a Glance
- Tasks: Conduct research on RF signals using AI techniques for signal recognition and manipulation.
- Company: Leading tech firm focused on innovative signal research.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Exciting role with potential for career advancement in a dynamic environment.
- Why this job: Join a cutting-edge team and make a real impact in AI-driven signal research.
- Qualifications: PhD or equivalent experience in relevant field, strong Python and ML skills required.
The predicted salary is between 63000 - 77000 £ per year.
ECM Selection is seeking a research-focused position for three years, working with sensor data in the RF signals domain.
You will survey, develop and apply modern techniques, including the use of AI, for recognition, identification, localisation and manipulation of relevant signals.
A Ph D or equivalent experience is required, with UK security clearance eligibility.
Hybrid work is likely, with time spent at the organisation’s central London research offices and strong Python/ML skills emphasized.
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RF Data Scientist — AI-Driven Signal Research employer: ECM Selection
This defence company is an excellent employer, offering a dynamic work environment where talented electronics engineers can thrive. With a strong focus on employee growth through mentorship and project leadership opportunities, the company fosters a collaborative culture that values innovation in high-stakes projects. Located just north of Cheltenham, employees benefit from competitive remuneration packages, including regular salary reviews and a generous pension scheme, making it a rewarding place to build a meaningful career.
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We think this is how you could land RF Data Scientist — AI-Driven Signal Research
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We think you need these skills to ace RF Data Scientist — AI-Driven Signal Research
Some tips for your application 🫡
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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.
