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- Tasks: Develop machine learning models for molecular analysis and collaborate with scientists.
- Company: Join a leading R&D team at the forefront of AI/ML innovation in biological data.
- Benefits: Enjoy competitive salary, performance bonuses, private healthcare, and a generous pension scheme.
- Why this job: Make a real impact in DNA/RNA/protein analysis while working in a collaborative environment.
- Qualifications: PhD or equivalent in Computational Biology, Computer Science, or Bioinformatics required.
- Other info: Work in a stunning campus with a strong mission-led culture.
The predicted salary is between 48000 - 72000 £ per year.
We are hiring for a Machine Learning Researcher to join its growing R&D function. This is a unique opportunity to apply cutting-edge machine learning techniques to solve meaningful challenges in the molecular analysis and sequencing space. You’ll collaborate with cross-functional teams to help shape next-generation tools and approaches for analysing complex biological data.
This Role Will Offer You:
- The chance to work at the forefront of scientific research and AI/ML innovation
- A highly collaborative, interdisciplinary team environment
- The opportunity to contribute to impactful projects in DNA/RNA/protein analysis
- A competitive salary and comprehensive benefits including performance bonuses, private healthcare, and a generous pension scheme
- A stunning campus location with landscaped surroundings and a strong mission-led culture
Your Responsibilities:
- Develop and apply machine learning models to advance molecular sensing and biomolecule modelling
- Collaborate closely with scientists and engineers to drive innovation across sequencing technologies
- Create and optimise tools tailored to nanopore and bioinformatics applications
- Present research findings clearly to both technical and non-technical stakeholders
- Contribute to the deployment of robust, user-facing tools and pipelines
You Will Need:
- A PhD (or equivalent experience) in a relevant field such as Computational Biology, Computer Science, Bioinformatics or similar
- Strong knowledge of biomolecular modelling, structural prediction, small molecule docking and/or biomolecule design
- Experience in prototyping and deploying algorithms in a scientific or engineering context
- Excellent communication and collaboration skills
- Strong programming skills and familiarity with software engineering best practices
Machine Learning Researcher employer: BioTalent
Contact Detail:
BioTalent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Researcher
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning techniques, especially those related to molecular analysis. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of computational biology and bioinformatics. Attend relevant conferences or webinars where you can meet potential colleagues and learn about their work, which could give you insights into the company’s projects.
✨Tip Number 3
Prepare to discuss your previous research and projects in detail, particularly those that involved machine learning applications. Be ready to explain your thought process and the impact of your work on the field.
✨Tip Number 4
Showcase your collaboration skills by highlighting any interdisciplinary projects you've worked on. Emphasising your ability to work with scientists and engineers will demonstrate that you're a good fit for the team-oriented environment at StudySmarter.
We think you need these skills to ace Machine Learning Researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, computational biology, and any specific projects related to biomolecular modelling. Use keywords from the job description to align your skills with what the company is looking for.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and its applications in molecular analysis. Mention specific experiences that demonstrate your ability to collaborate with cross-functional teams and your understanding of the challenges in DNA/RNA/protein analysis.
Showcase Your Research Experience: If you have published research or developed algorithms, summarise these achievements clearly. Highlight how your work has contributed to advancements in the field and how it relates to the responsibilities outlined in the job description.
Prepare for Technical Questions: Anticipate technical questions related to machine learning models, programming skills, and bioinformatics tools. Be ready to discuss your approach to problem-solving and how you would apply your knowledge to the company's projects.
How to prepare for a job interview at BioTalent
✨Showcase Your Technical Expertise
Be prepared to discuss your PhD research and any relevant projects in detail. Highlight your experience with machine learning models, biomolecular modelling, and any specific algorithms you've developed or deployed.
✨Demonstrate Collaboration Skills
Since the role involves working closely with scientists and engineers, be ready to share examples of how you've successfully collaborated in interdisciplinary teams. Emphasise your ability to communicate complex ideas to both technical and non-technical audiences.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've encountered in your previous work and how you approached them, particularly in the context of molecular analysis and sequencing.
✨Familiarise Yourself with Current Trends
Stay updated on the latest advancements in AI/ML and their applications in biological data analysis. Being knowledgeable about current trends will not only impress your interviewers but also show your passion for the field.
