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- Tasks: Join a team to analyse mental health data and explore health inequalities.
- Company: UCL Division of Psychiatry is at the forefront of mental health research.
- Benefits: Enjoy 41 days holiday, a pension scheme, and wellness perks like an on-site gym.
- Why this job: Shape impactful research while collaborating with top health data experts.
- Qualifications: PhD (or near completion) in relevant fields; strong data analysis skills required.
- Other info: Initial 1-year contract with potential funding for up to 4 years.
The predicted salary is between 28800 - 48000 £ per year.
About the role
We are seeking an enthusiastic individual with an interest in data science and health informatics in mental health to work on a national project with DATAMIND – the mental health data hub, and the HDR-UK Mental Health Driver Programme. Our aim is to embed mental health in other HDR-UK Driver Programmes, for example, the Big Data for Complex Disease Driver. This is an exciting programme of research funded by UKRI, exploring the interface between physical and mental health. The post will be based in UCL Division of Psychiatry. The individual will work within a team of Research Fellows and PhD students focused on routine data and electronic health records to understand the interface of physical and mental health. The DATAMIND project will utilize several UK routine data sets to describe available data sources. The work includes an exemplar project on common mental disorders (e.g., depression), cardiovascular disease, and cancer, with scope for the candidate to shape this project based on their interests. We are particularly interested in data sources that can reveal relationships between health inequalities, ethnic inequalities, underserved groups, and co-occurring physical health issues. The role is initially a 1-year fixed-term contract, with potential funding for up to 4 years.
About you
You should have a PhD (or near completion) in epidemiology, health informatics, data science, or a related field, with a strong interest in analyzing large datasets. Proficiency with statistical software tools (e.g., R, STATA, Python, Julia) and experience running applications on large computer clusters are essential. Experience in epidemiology and bioinformatics, especially accessing, curating, cleaning, analyzing, and interpreting large routine and electronic health record datasets from diverse sources, is highly advantageous. The ideal candidate will be motivated, resourceful, and independent. We support career development and encourage independence. The successful applicant will have opportunities to collaborate with leading UK health data science experts and enhance the visibility of mental health research.
What we offer
In addition to the exciting work, we offer several benefits, including:
- 41 days holiday (27 days annual leave, 8 bank holidays, and 6 closure days)
- Defined benefit career average revalued earnings pension scheme (CARE)
- Cycle to work scheme and season ticket loan
- On-site gym
- Enhanced maternity, paternity, and adoption pay
- Employee assistance programme: Staff Support Service
Full details of staff benefits can be found here.
Research Fellow in Mental Health Epidemiology/Data Science employer: TN United Kingdom
Contact Detail:
TN United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Fellow in Mental Health Epidemiology/Data Science
✨Tip Number 1
Network with professionals in the field of mental health epidemiology and data science. Attend relevant conferences, webinars, or workshops to meet potential colleagues and mentors who can provide insights into the role and possibly refer you.
✨Tip Number 2
Familiarise yourself with the latest research and developments in mental health data science. Being well-versed in current trends and methodologies will not only enhance your knowledge but also demonstrate your passion for the field during interviews.
✨Tip Number 3
Engage with online communities and forums related to health informatics and epidemiology. Participating in discussions can help you gain valuable insights and may even lead to connections that could support your application.
✨Tip Number 4
Consider reaching out to current or former employees of the UCL Division of Psychiatry. They can provide first-hand information about the work environment and expectations, which can be beneficial when preparing for interviews.
We think you need these skills to ace Research Fellow in Mental Health Epidemiology/Data Science
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in epidemiology, health informatics, and data science. Emphasise your proficiency with statistical software tools like R, STATA, Python, or Julia, as well as any experience with large datasets.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the specific projects mentioned in the job description. Discuss how your background aligns with the goals of the DATAMIND project and your interest in mental health research.
Showcase Relevant Projects: If you have worked on similar projects or have experience with health data analysis, be sure to include these in your application. Highlight any specific outcomes or contributions you made that relate to the role.
Proofread Your Application: Before submitting, carefully proofread your application materials for any errors or typos. A polished application reflects your attention to detail and professionalism, which are crucial in research roles.
How to prepare for a job interview at TN United Kingdom
✨Showcase Your Data Skills
Make sure to highlight your proficiency with statistical software tools like R, STATA, Python, or Julia. Be prepared to discuss specific projects where you've used these tools to analyse large datasets, as this will demonstrate your technical capabilities.
✨Understand the Project's Goals
Familiarise yourself with the DATAMIND project and its objectives. Being able to articulate how your interests align with the project's focus on mental health and data science will show your enthusiasm and commitment to the role.
✨Discuss Health Inequalities
Since the role involves exploring health inequalities, be ready to discuss your understanding of this topic. Share any relevant experiences or insights you have regarding ethnic inequalities and underserved groups in health research.
✨Demonstrate Independence and Motivation
The ideal candidate is described as motivated and independent. Prepare examples from your past work or studies that illustrate your ability to work autonomously and take initiative, as this will resonate well with the interviewers.
