At a Glance
- Tasks: Investigate zoonotic disease pathways between bats and humans with a dynamic research team.
- Company: Join the University of Sussex, a leader in STEMM research and diversity.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Diverse and inclusive environment with excellent career advancement opportunities.
- Why this job: Make a real impact on public health by studying infectious diseases in wildlife.
- Qualifications: PhD in infectious disease modelling and strong quantitative skills required.
The predicted salary is between 38784 - 38784 € per year.
Location: Brighton, UK
Hours: Full-time considered up to a maximum of 1.0 FTE (37.5 hours). Requests for flexible working options will be considered (subject to business need).
Salary: Grade 7 starting at £38,784 per annum, pro‑rated if part‑time.
Contract Type: Fixed Term Contract
Responsibilities:
- Assess potential zoonotic disease transmission pathways between bats and humans as part of the OneBAT consortium funded by Horizon Europe.
- Collaborate with an interdisciplinary network of researchers in ecology, epidemiology, and public health.
- Analyse a unique longitudinal dataset from maternity roosts in five European countries, integrating molecular and serological data to characterise infection dynamics of lyssaviruses, filoviruses, and coronaviruses.
- Apply advanced statistical and mechanistic modelling approaches, including fitting compartmental (SIR‑type) models to real‑world surveillance data from wild animal populations.
- Work closely with field ecologists and laboratory scientists across the consortium.
- Contribute to understanding how viruses persist and spread in natural host populations, with implications for predicting and mitigating zoonotic risks.
Qualifications:
- PhD or equivalent experience in infectious disease modelling with strong quantitative skills.
- Experience fitting compartmental models to surveillance data and working with complex longitudinal datasets.
- High competency in R; familiarity with Python and efficient data‑management workflows is advantageous.
- Ability to interpret molecular and serological data and communicate research methods clearly to non‑specialists.
- Strong track record of effective teamwork and excellent interpersonal skills.
- Understanding of infectious disease epidemiology in wild populations and ecological or epidemiological modelling approaches is preferred.
Equality and diversity:
The University is committed to equality and valuing diversity; applications are particularly welcomed from women and black and minority ethnic candidates, who are under‑represented in academic posts in Science, Technology, Engineering, Medicine and Mathematics (STEMM) at Sussex. The University of Sussex values the diversity of its staff and students, and we welcome applicants from all backgrounds.
Visa and sponsorship:
This role has been assigned an eligible SOC code and meets the salary requirements for Skilled Worker Sponsorship if full‑time and appointed at Grade 7.4. This position may be subject to ATAS clearance if you require visa sponsorship (code: CAH03‑01‑03 - Ecology and Environmental Biology). The University requires that work undertaken for the University is performed in the UK.
Research Fellow in Epidemiological Modelling in Bats in Brighton employer: Brighton and Sussex Medical School
The University of Sussex is an exceptional employer, offering a vibrant work culture that fosters collaboration and innovation in the field of epidemiological research. With a commitment to equality and diversity, the university provides ample opportunities for professional growth and development, particularly in interdisciplinary projects like the OneBAT consortium. Located in the picturesque city of Brighton, employees enjoy a supportive environment with flexible working options, making it an ideal place for those seeking meaningful and impactful careers in academia.
Contact Detail:
Brighton and Sussex Medical School Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Research Fellow in Epidemiological Modelling in Bats in Brighton
✨Tip Number 1
Network like a pro! Reach out to your connections in the field of epidemiology and ecology. Attend relevant conferences or webinars, and don’t be shy about introducing yourself to potential collaborators or mentors. You never know who might have a lead on that perfect Research Fellow position!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your previous work with statistical modelling and data analysis. If you’ve got experience with R and Python, highlight specific projects where you applied these skills. This will give you an edge when discussing your qualifications during interviews.
✨Tip Number 3
Practice makes perfect! Conduct mock interviews with friends or colleagues to get comfortable discussing your research and methodologies. Focus on explaining complex concepts in simple terms, as you’ll need to communicate effectively with non-specialists in your future role.
✨Tip Number 4
Apply through our website! We encourage you to submit your application directly on our platform. It’s a great way to ensure your application gets the attention it deserves, and you can easily keep track of your submissions and updates.
We think you need these skills to ace Research Fellow in Epidemiological Modelling in Bats in Brighton
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Research Fellow position. Highlight your experience in infectious disease modelling and any relevant projects you've worked on, especially those involving bats or zoonotic diseases. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about epidemiological modelling and how you can contribute to the OneBAT consortium. Be sure to mention your teamwork skills and any interdisciplinary collaborations you've been part of.
Showcase Your Technical Skills:Since this role requires strong quantitative skills, make sure to highlight your proficiency in R and any experience with Python. If you've worked with complex datasets or fitted compartmental models, give us the details! We love seeing concrete examples of your technical prowess.
Apply Through Our Website:Don't forget to apply through our website! It’s the best way to ensure your application gets to us directly. Plus, it shows you're keen on joining our team at StudySmarter. We can't wait to see what you bring to the table!
How to prepare for a job interview at Brighton and Sussex Medical School
✨Know Your Stuff
Make sure you brush up on your knowledge of zoonotic diseases and the specific modelling techniques mentioned in the job description. Be ready to discuss how you've applied advanced statistical methods in your previous work, especially with compartmental models.
✨Show Your Team Spirit
This role involves collaboration with various researchers, so highlight your teamwork skills. Prepare examples of past projects where you worked effectively in a team, particularly in interdisciplinary settings, and how you communicated complex data to non-specialists.
✨Get Familiar with the Data
Since you'll be analysing longitudinal datasets, it’s crucial to demonstrate your experience with R and any familiarity with Python. Bring along examples of your data management workflows and be prepared to discuss how you’ve tackled challenges in data analysis.
✨Ask Insightful Questions
Prepare thoughtful questions about the OneBAT consortium and its goals. This shows your genuine interest in the project and helps you understand how your role will contribute to the bigger picture. It’s also a great way to engage with the interviewers!
