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For Companies At a Glance
- Tasks: Design NLP pipelines and develop ML models to accelerate materials science research.
- Company: Durham University, a leader in multidisciplinary research.
- Benefits: Competitive salary, collaborative environment, and opportunities for impactful research.
- Why this job: Join a cutting-edge project that merges tech with science to drive innovation.
- Qualifications: Experience in machine learning, natural language processing, and Python programming.
- Other info: Dynamic research setting with potential for significant career advancement.
The predicted salary is between 36000 - 60000 £ per year.
The Role
Applications are invited for a Research Associate in Machine Learning and Natural Language Processing for Materials Science.
Project Overview
The project focuses on building a database and on combining advanced ML and NLP approaches to accelerate discovery in Molecular Solid Solutions (MoSS). Data will be gathered collectively during the course of the project. NLP techniques will be used to automatically extract key data points from published papers and reports, building and enriching a comprehensive MoSS database. Machine Learning will then be applied to this database, alongside quantum chemistry methods, to predict MoSS formation, model dopant effects on crystal structures, and identify optimal dopants for tuning host compounds. The project is highly multidisciplinary, linking computational and physical chemistry, physics, and computer science at Durham University and partner institutions.
Responsibilities
- Design and implement NLP pipelines for literature mining.
- Select, adapt, and develop ML models, predictive models in PyTorch, and interpretable methods such as SHAP and causal inference.
- Produce python code for advanced scientific data processing and implement it in the project data pipelines.
- Serve as the project data champion.
- Contribute actively to high‑quality research outputs, including publications, software tools, and follow‑on grant proposals.
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PDRA in Machine Learning and Natural Language Processing for Materials Science employer: Durham University
Contact Detail:
Durham University Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land PDRA in Machine Learning and Natural Language Processing for Materials Science
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of Machine Learning and Natural Language Processing. Attend relevant meetups or webinars, and don’t be shy to ask questions. 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 NLP and ML. Whether it’s GitHub repos or a personal website, having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with Python, PyTorch, and any relevant ML models. Practise explaining complex concepts in simple terms – it shows you really understand your stuff!
✨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 PDRA in Machine Learning and Natural Language Processing for Materials Science
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role. Highlight your experience with Machine Learning and Natural Language Processing, especially any projects related to materials science. We want to see how your skills fit into our multidisciplinary project!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about this project and how your background makes you a perfect fit. Don’t forget to mention any relevant research outputs or software tools you've developed.
Showcase Your Technical Skills: Since this role involves Python coding and ML model development, be sure to showcase your technical skills. Mention specific libraries or frameworks you’ve worked with, like PyTorch, and any experience with NLP techniques that could benefit our project.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Durham University
✨Know Your ML and NLP Stuff
Make sure you brush up on your machine learning and natural language processing knowledge. Be ready to discuss specific algorithms, models, and techniques you've used in the past, especially in relation to literature mining and data extraction.
✨Show Off Your Coding Skills
Since you'll be producing Python code for scientific data processing, it’s crucial to demonstrate your coding abilities. Bring examples of your previous work or projects where you implemented ML models in PyTorch, and be prepared to talk through your thought process.
✨Understand the Project's Multidisciplinary Nature
This role links various fields like computational chemistry and physics. Familiarise yourself with how these disciplines intersect with machine learning and NLP. Being able to articulate this connection will show your enthusiasm and understanding of the project.
✨Prepare Questions About the Role
Interviews are a two-way street! Prepare insightful questions about the project, team dynamics, and future research directions. This not only shows your interest but also helps you gauge if the role is the right fit for you.
