At a Glance
- Tasks: Analyse data from wearable sensors to improve maternal health outcomes globally.
- Company: Join the University of Edinburgh's innovative Centre for Medical Informatics.
- Benefits: Gain valuable research experience and contribute to impactful global health initiatives.
- Other info: Be part of a dynamic team working on an international study across multiple countries.
- Why this job: Make a real difference in maternal and neonatal health using cutting-edge AI technology.
- Qualifications: Experience in data analysis and a passion for global health research.
The predicted salary is between 29700 - 36300 £ per year.
The Centre for Medical Informatics at the Usher Institute within The University of Edinburgh is looking for a Research Fellow (Data Analysis) to work on the IMPALA 2 trial, using wearable sensors and data-driven methods to analyse near-real-time data in a large international study.
You will contribute to developing, evaluating, and deploying generative AI approaches to predict maternal and neonatal complications across 13,400 women in 30 hospitals across four countries.
Research Fellow: Data Analytics for Global Maternal Health employer: The University of Edinburgh
The University of Edinburgh is an exceptional employer, offering a dynamic work environment where innovation meets inclusivity. With a competitive salary and comprehensive benefits, employees are encouraged to grow professionally while contributing to cutting-edge research in cyber-security. Located in Glasgow, the university fosters a vibrant community that values diversity and promotes equal opportunities for all staff members.
Contact Details:
The University of Edinburgh Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Research Fellow: Data Analytics for Global Maternal Health
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We think you need these skills to ace Research Fellow: Data Analytics for Global Maternal Health
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at The University of Edinburgh, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to The University of Edinburgh, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab The University of Edinburgh’s attention and show the tangible impact of your work.
How to prepare for a job interview at The University of Edinburgh
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at The University of Edinburgh.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at The University of Edinburgh.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at The University of Edinburgh.
