PhD Student in Forecasting Resistance Spread and Epidemiological Impact
Indiana, Indiana County, Pennsylvania, 15705, USA
Listed on 2026-01-02
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Research/Development
Research Scientist, Data Scientist
Location: Indiana
Organisation/Company Swiss TPH Research Field Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Switzerland Final date to receive applications 18 Jan 2026 - 23:59 (Europe/Zurich) Type of Contract Temporary Job Status Full-time Hours Per Week 42.5 Offer Starting Date 1 Mar 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure?
No
Malaria, transmitted by Anopheles mosquitoes, caused over a million deaths annually in the early 2000s. Insecticide-treated bed nets have since helped halve global mortality, but this progress is threatened by rising insecticide resistance. We build quantitative, data-driven models to forecast the spread and impact of resistance, guiding the optimal use of new insecticide-treated nets.
YOUR VARIOUSRESPONSIBILITIES INCLUDE:
- Drive your own PhD project on developing mechanistic/process-based, spatially explicit models of insecticide resistance spread and impact, using Bayesian statistics, mathematical modelling, machine learning, and quantitative genetics
- Implement resistance-spread models using state-of-the-art programming practices with version control; calibrate them to available data; integrate them with our epidemiological simulation platform; and evaluate resistance-management strategies to maintain insecticide effectiveness
- Communicate your research through peer-reviewed publications, conference presentations, workshops, and regular meetings with collaborators
- MSc degree (or nearing completion) with excellent grades in a quantitative field (e.g. statistics, mathematics, computer science, physics) or in biology/environmental sciences/epidemiology with strong quantitative training
- Strong analytical skills for developing mathematical/statistical methods and strong programming skills for implementing them. Experience in R, Python, Stan, HPC environments, and Git is an advantage
- A demonstrated interest or strong enthusiasm for delving into Bayesian statistics, modelling, resistance management, evolutionary processes, and public health
- Ideally, prior experience in Bayesian data analysis, spatial statistics, evolutionary biology, computational biology, disease modelling, environmental modelling, analysis of genetic/genomic data, or quantitative genetics
- Ability to manage your work independently and collaboratively, including planning, documenting, and communicating your work effectively
- Ability to communicate research effectively in spoken and written English
- Direct and dedicated supervision led by Dr. Adrian Denz, with a strong commitment to supporting you in achieving research excellence in Bayesian forecasting of resistance dynamics as well as in developing your academic writing skills and scientific independence
- Close exchange with renowned malaria researchers at Swiss TPH as well as international project partners
- A multidisciplinary, international, and agile research institution with strong links to international policy makers, national health ministries, and industry, and excellent computational infrastructure with access to the HPC cluster at the University of Basel, alongside an active student community
- A state-of-the-art workspace in the new Swiss TPH building with an on-site canteen, located on the dynamic Base Link site in Allschwil near Basel. Basel is a walkable, bikeable city with high quality of life bordering France and Germany, and an international hub for pharmaceutical research and culture.
- Enrollment as a PhD student at the University of Basel, with access to university courses, Swiss Institute of Bioinformatics training, continuing education opportunities, and university sports facilities
- Internationally competitive salary and benefits according to SNSF and University of Basel regulations, fully funded for 3 years via an SNSF Ambizione grant
CONDITIONS:
- Start Date:
as soon as mutually agreed, between March and October 2026 - Duration: 3 years
- Percentage: 100%, primarily on-site with flexibility for home office
- Travel required:
some travel…
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