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- Tasks: Develop ML models and design systems that merge biology with cutting-edge technology.
- Company: VC-backed biotech startup focused on innovation and collaboration.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Join a dynamic team and make a real impact in biotechnology.
- Why this job: Shape the future of synthetic genomics while working with passionate scientists.
- Qualifications: BSc or MSc in engineering, solid ML experience, and a curiosity for biology.
The predicted salary is between 50000 - 70000 £ per year.
A VC-backed biotechnology startup is looking for an ML engineer to develop production systems that bridge biology and machine learning. You will implement state-of-the-art models, design experimentation infrastructures, and refine processes in a collaborative environment.
The ideal candidate has:
- A BSc or MSc in an engineering field
- Solid ML experience
- A deep curiosity about biology
This is an exciting opportunity to shape the future of synthetic genomics and work closely with experimental scientists.
ML Engineer for Genomics & Biofactories — Production Systems in Peterborough employer: Constructive Bio
Contact Detail:
Constructive Bio Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer for Genomics & Biofactories — Production Systems in Peterborough
✨Tip Number 1
Network like a pro! Reach out to people in the biotech and ML fields on LinkedIn. Join relevant groups and engage in discussions to get your name out there and show your passion for the industry.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those related to biology or production systems. 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 both technical and biological concepts. Be ready to discuss how you can bridge the gap between machine learning and experimental science—this is key for the role!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals who want to make an impact in synthetic genomics. Your dream job could be just a click away!
We think you need these skills to ace ML Engineer for Genomics & Biofactories — Production Systems in Peterborough
Some tips for your application 🫡
Show Your Passion for Biology: When you're writing your application, let your enthusiasm for biology shine through! We want to see how your curiosity about the field drives your work in machine learning. Share any relevant projects or experiences that highlight this passion.
Highlight Your ML Experience: Make sure to detail your solid ML experience in your application. We’re looking for someone who can implement state-of-the-art models, so don’t hold back on showcasing your skills and any specific projects you've worked on that relate to this.
Collaborative Spirit is Key: Since we work closely with experimental scientists, it’s important to convey your ability to collaborate effectively. In your application, mention any teamwork experiences and how you’ve contributed to group projects in the past.
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’re considered for this exciting opportunity. Don’t miss out on shaping the future of synthetic genomics with us!
How to prepare for a job interview at Constructive Bio
✨Know Your ML Models
Make sure you brush up on the latest machine learning models relevant to genomics. Be ready to discuss how you've implemented these in past projects and how they can be applied to production systems in a biotech context.
✨Show Your Curiosity About Biology
Since this role bridges biology and machine learning, demonstrate your interest in biological concepts. Prepare some questions about the company's research focus and how ML can enhance their work in synthetic genomics.
✨Collaborative Mindset
This position involves working closely with experimental scientists, so highlight your teamwork skills. Share examples of how you've successfully collaborated in previous roles, especially in interdisciplinary teams.
✨Prepare for Technical Challenges
Expect technical questions or challenges during the interview. Practice explaining your thought process when solving problems, and be ready to discuss how you would design experimentation infrastructures in a practical setting.