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- Tasks: Lead partnerships with pharma companies and manage AI deployments in R&D.
- Company: Leading UK biotechnology firm at the forefront of innovation.
- Benefits: Competitive salary, flexible work arrangements, and remote opportunities.
- Other info: Join a dynamic team and contribute to groundbreaking projects.
- Why this job: Make a real impact in biotech by applying AI to revolutionise healthcare.
- Qualifications: PhD in Computational Biology or related field, with machine learning expertise.
The predicted salary is between 60000 - 80000 £ per year.
A leading biotechnology firm based in the UK is looking for an Applied AI Scientist to lead partnerships with pharmaceutical companies. The ideal candidate will have a PhD in Computational Biology or a related field and expertise in machine learning.
Responsibilities include:
- Managing partner deployments
- Consulting on R&D applications
- Synthesizing client feedback into product features
This role offers a competitive salary and flexible work arrangements.
Pharma AI Partnerships Scientist (Remote) in London employer: Bioptimus
Contact Detail:
Bioptimus Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Pharma AI Partnerships Scientist (Remote) in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the biotech and AI sectors on LinkedIn. Join relevant groups and engage in discussions to get your name out there.
✨Tip Number 2
Showcase your expertise! Create a portfolio or a personal website where you can highlight your projects, especially those related to machine learning and computational biology. This will make you stand out!
✨Tip Number 3
Prepare for interviews by practising common questions in the biotech and AI fields. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We have loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets noticed.
We think you need these skills to ace Pharma AI Partnerships Scientist (Remote) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your PhD and any relevant experience in Computational Biology or machine learning. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI in pharmaceuticals and how your background makes you the perfect fit for this role. Let us know what excites you about working with us!
Showcase Your Partnership Experience: If you've managed partnerships or collaborations before, make sure to highlight those experiences. We’re looking for someone who can effectively manage partner deployments, so any relevant examples will help us see your potential.
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 the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Bioptimus
✨Know Your Stuff
Make sure you brush up on your knowledge of computational biology and machine learning. Be ready to discuss specific projects or research you've done in these areas, as well as how they relate to the pharmaceutical industry.
✨Showcase Your Partnership Skills
Since this role involves leading partnerships, think of examples where you've successfully collaborated with others. Prepare to discuss how you managed those relationships and what strategies you used to ensure successful outcomes.
✨Understand Their Needs
Research the biotechnology firm and their current projects. Understand their goals and challenges in the AI space, so you can tailor your responses to show how you can help them achieve their objectives.
✨Feedback is Key
Be prepared to talk about how you've incorporated client feedback into your work. Think of specific instances where you adapted your approach based on user input, as this will demonstrate your ability to synthesise feedback into actionable product features.