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- Tasks: Conduct research in probabilistic modelling and Bayesian optimisation for innovative AI solutions.
- Company: Reputable UK recruitment firm with a focus on cutting-edge machine learning.
- Benefits: Opportunity to work in a dynamic AI lab with collaborative teams.
- Why this job: Join a pioneering team and contribute to impactful machine learning research.
- Qualifications: PhD in a related field and strong numerical programming skills required.
- Other info: Unique chance to work on customer-facing projects in a vibrant environment.
The predicted salary is between 36000 - 60000 £ per year.
A reputable UK recruitment firm is seeking a researcher to join an AI lab in Cambridge focused on machine learning solutions. The role involves conducting research in probabilistic modelling, Bayesian optimisation, and working closely with teams on product and customer-facing projects.
Candidates should hold a PhD in a related field and have a strong background in numerical programming and a collaborative mindset. This is a unique opportunity to contribute to cutting-edge ML research.
Probabilistic ML Research Scientist – Bayesian Optimisation in Cambridge employer: TEC Partners - Technical Recruitment Specialists
Contact Detail:
TEC Partners - Technical Recruitment Specialists Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Probabilistic ML Research Scientist – Bayesian Optimisation in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and machine learning community, especially those working in Cambridge. Attend meetups or webinars to make connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your research projects, especially those related to probabilistic modelling and Bayesian optimisation. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your past research and how it relates to the role. We want to see your passion for ML and collaboration!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect with us directly.
We think you need these skills to ace Probabilistic ML Research Scientist – Bayesian Optimisation in Cambridge
Some tips for your application 🫡
Show Off Your Research Skills: Make sure to highlight your research experience in probabilistic modelling and Bayesian optimisation. We want to see how your PhD work aligns with our focus on cutting-edge ML solutions.
Demonstrate Your Programming Prowess: Since a strong background in numerical programming is key, don’t forget to mention the languages and tools you’re proficient in. We love seeing practical examples of your coding skills!
Emphasise Collaboration: This role involves working closely with teams, so let us know about your collaborative experiences. Share examples of how you've successfully worked with others on research or product projects.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on this unique opportunity!
How to prepare for a job interview at TEC Partners - Technical Recruitment Specialists
✨Know Your Bayesian Basics
Make sure you brush up on your knowledge of Bayesian optimisation and probabilistic modelling. Be prepared to discuss your previous research and how it relates to the role. Having specific examples ready will show your depth of understanding and passion for the subject.
✨Showcase Your Programming Skills
Since a strong background in numerical programming is essential, be ready to talk about the programming languages and tools you’ve used in your projects. If possible, bring along a portfolio or examples of your work that demonstrate your coding skills and problem-solving abilities.
✨Collaborative Mindset is Key
This role involves working closely with teams, so highlight your experience in collaborative projects. Share examples of how you’ve successfully worked with others, resolved conflicts, or contributed to team goals. This will show that you’re not just a brilliant researcher but also a great team player.
✨Prepare Questions About the Lab's Work
Research the AI lab and its current projects before the interview. Prepare thoughtful questions that show your interest in their work and how you can contribute. This not only demonstrates your enthusiasm but also helps you assess if the lab is the right fit for you.
