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- Tasks: Build and maintain predictive models to revolutionise drug discovery.
- Company: Leading global healthcare company focused on innovation.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Make a real-world impact in healthcare with cutting-edge technology.
- Qualifications: Relevant degree and 4-6 years of experience in Python and AI/ML.
- Other info: Join a dynamic team in a fast-paced environment.
The predicted salary is between 36000 - 60000 £ per year.
A leading global healthcare company is seeking a Machine Learning Engineer to build, deploy, and maintain predictive models that aid drug discovery. In this role, you will develop modelling code, train models, and work in an agile team, ensuring high technical quality.
Ideal candidates hold a relevant degree, have 4-6 years of experience, and are proficient with Python and AI/ML frameworks. This dynamic position offers an opportunity to make a real-world impact in healthcare.
Machine Learning Engineer - Drug Discovery AI in London employer: Novo Nordisk A/S
Contact Detail:
Novo Nordisk A/S Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Drug Discovery AI in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the healthcare and AI/ML fields on LinkedIn. Join relevant groups and participate in discussions to get your name out there.
✨Tip Number 2
Showcase your skills! Create a portfolio of your projects, especially those related to drug discovery or predictive modelling. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and AI/ML frameworks. Practice coding challenges and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to show your interest in joining our team.
We think you need these skills to ace Machine Learning Engineer - Drug Discovery AI in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and AI/ML frameworks. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about drug discovery and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any cool machine learning projects, make sure to mention them! We love seeing practical applications of your skills, especially if they relate to healthcare or predictive modelling.
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 any important updates from our team!
How to prepare for a job interview at Novo Nordisk A/S
✨Know Your Models Inside Out
Make sure you can discuss the predictive models you've built in detail. Be ready to explain your approach to model selection, training, and evaluation. This shows your technical depth and understanding of the drug discovery process.
✨Brush Up on Python and Frameworks
Since proficiency in Python and AI/ML frameworks is key, review your coding skills and be prepared to solve problems on the spot. Practising common algorithms and their implementations will help you demonstrate your expertise.
✨Showcase Your Teamwork Skills
This role involves working in an agile team, so be ready to share examples of how you've collaborated with others. Highlight your experience in agile methodologies and how you contribute to a positive team dynamic.
✨Prepare for Real-World Applications
Understand the impact of your work in healthcare. Be prepared to discuss how your machine learning solutions can aid drug discovery and improve patient outcomes. This will show your passion for the field and your commitment to making a difference.
