At a Glance
- Tasks: Develop NLP and ML methods to extract health data outcomes and collaborate with a multidisciplinary team.
- Company: The University of Liverpool, a leader in Health Data Science research.
- Benefits: Gain valuable experience, work in a supportive environment, and contribute to impactful health projects.
- Other info: Join a dynamic team focused on innovative health solutions.
- Why this job: Make a difference in health data science while advancing your research career.
- Qualifications: PhD or Master's with AI/ML health data experience and strong programming skills.
The predicted salary is between 29700 - 36300 £ per year.
The University of Liverpool is seeking a Postdoctoral Research Associate or Research Associate to join the Outcomes Tracker project in Health Data Science. You will develop NLP and ML methods to extract outcomes from registries, protocols and publications, and work with a multidisciplinary team to curate data and build reproducible software.
You should have a PhD (or near completion) or a Master’s with significant AI/ML health data experience, plus strong programming and a commitment to the project.
Postdoc: NLP/ML for Health Data Outcomes in Liverpool employer: Corehr
As a leading research institution, we offer an exceptional environment for postdoctoral researchers to thrive, particularly in the vibrant city of Liverpool. Our commitment to collaboration across prestigious universities fosters a dynamic work culture that prioritises innovation and inclusivity, while our hybrid working model supports a healthy work-life balance. With ample opportunities for professional growth and a focus on diversity, we are dedicated to creating a meaningful and rewarding experience for all employees.
StudySmarter Expert Advice🤫
We think this is how you could land Postdoc: NLP/ML for Health Data Outcomes in Liverpool
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We think you need these skills to ace Postdoc: NLP/ML for Health Data Outcomes in Liverpool
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Corehr, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Corehr. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Corehr
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
