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- Tasks: Develop machine learning pipelines to extract drug side effects and enhance AI/ML methodologies.
- Company: Leading UK research institution collaborating with major pharmaceutical partners.
- Benefits: Competitive salary, research opportunities, and a dynamic team environment.
- Why this job: Make a real impact in drug discovery while working with cutting-edge technology.
- Qualifications: Postgraduate degree in computational linguistics or bioinformatics required.
- Other info: Join a dynamic team focused on impactful research.
The predicted salary is between 36000 - 60000 £ per year.
A leading UK research institution is seeking an NLP Data Scientist / Scientific Data Engineer to develop machine learning pipelines for extracting drug side effects and enhance AI/ML methodologies. The role involves collaboration with major pharmaceutical partners and will require expertise in language models, data analysis, and Python. The ideal candidate should possess a postgraduate degree in computational linguistics or bioinformatics. Join a dynamic team to deliver impactful research in drug discovery.
NLP & ML Scientist for Biomedical Safety Pipelines employer: European Bioinformatics Institute | EMBL-EBI
Contact Detail:
European Bioinformatics Institute | EMBL-EBI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land NLP & ML Scientist for Biomedical Safety Pipelines
✨Tip Number 1
Network like a pro! Reach out to professionals in the NLP and ML fields, especially those working in biomedical safety. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to machine learning pipelines and drug side effects. This will not only demonstrate your expertise but also give you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and understanding of language models. Practice coding challenges and be ready to explain your thought process clearly; it’s all about showing how you think!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace NLP & ML Scientist for Biomedical Safety Pipelines
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with NLP and ML, especially in the context of biomedical applications. We want to see how your skills align with the job description, so don’t hold back on showcasing relevant projects!
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 in computational linguistics or bioinformatics makes you a perfect fit for our team. Let us feel your enthusiasm!
Showcase Your Technical Skills: Since this role involves Python and machine learning pipelines, be sure to mention specific tools and frameworks you’ve worked with. We love seeing practical examples of your expertise, so don’t shy away from including any relevant projects or achievements.
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 gives you a chance to explore more about our dynamic team and impactful research!
How to prepare for a job interview at European Bioinformatics Institute | EMBL-EBI
✨Know Your NLP and ML Stuff
Make sure you brush up on your knowledge of natural language processing and machine learning techniques. Be ready to discuss specific projects you've worked on, especially those involving drug side effects or biomedical data. This will show that you’re not just familiar with the concepts but have practical experience too.
✨Showcase Your Python Skills
Since Python is a key requirement for this role, be prepared to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice writing clean, efficient code. Familiarise yourself with libraries like NLTK or TensorFlow that are relevant to NLP and ML.
✨Understand the Pharmaceutical Landscape
Research the pharmaceutical partners the institution collaborates with. Knowing their focus areas and recent developments can help you tailor your answers and show genuine interest in how your work could impact drug discovery.
✨Prepare Questions That Matter
Interviews are a two-way street, so think of insightful questions to ask about the team dynamics, ongoing projects, and future directions in AI/ML methodologies. This not only shows your enthusiasm but also helps you gauge if the role is the right fit for you.
