Postdoctoral positions in Infectious Disease Modelling (f/m/d), full-time

Joacim Rocklöv, Alexander von Humboldt Professor at Heidelberg University, is in the process of forming a cutting-edge research group studying the emergence of infectious diseases in a changing environment and climate. His group is positioned across faculties belonging both to the Heidelberg Institute of Global Health (HIGH) and the Interdisciplinary Centre for Scientific Computing (IWR). The group is looking for several postdocs working on scientific approaches to big data and data science for the development of applied epidemiological infectious disease models in relation to environmental data. The purpose is primarily to generate new scientific insights and knowledge across disciplines, but also to showcase and contribute to the development of new innovative tools for decision-making.
The positions are limited to 3 years, with the possibility of extension.

Your tasks:
The work may involve one or several of the following tasks:

• Study drivers of infectious disease emergence using global databases and data sciences approaches in relation to climate change
• Investigate disease risk and emergence of OneHealth and EcoHealth related disease threats in relation to environmental changes
• Project and forecast infectious disease outbreak potential and risks in relation to climate and non-climate drivers
• Develop and establish new models by integrating AI methodology with established process-based mathematical infectious disease models
• Develop and validate methods for image identification of disease vectors using visual learning techniques
• Utilize the wealth of data generated during the COVID-19 pandemic to identify critical factors contributing to local adaptive capacity and resilience to emerging infectious disease events
• To develop epidemiological infectious disease models based on machine learning in relation to explainable AI and causal inference
• Engage in data mining and environmental data processing and data curation
• Collaborate in projects with an interdisciplinary team of doctoral students and postdocs with different backgrounds and expertise
• Engage in proposal writing and networking

Your profile:

• PhD in mathematics, statistics, physics, data science, informatics, climatology, meteorology, environmental sciences, ecology, computer science, engineering or epidemiology or related field
• Strong interest in infectious disease dynamics and control
• Programming skills
• Modelling skills
• Management and curation of environmental and climate data will be a merit, but is not a required skill
• Prior experience within epidemiology or infectious disease is a merit, but is not a requirement
• Fluency in English in writing and spoken language
• Ability to work and collaborate in an interdisciplinary team

We offer:

• A stimulating international and interdisciplinary research environment with strong global networks
• Integration into a research team that is committed to deliver the highest standards of research in a fair, supportive and collaborative manner
• Research that contributes to saving lives and informing more efficient global health and environmental policy
• Excellent research facilities at Mathematikon INF 205 with access to state-of-the-art tools and infrastructure
• Salary according to TV-L
• Various training opportunities to broaden your expertise and (soft) skills
• A possibility to make exchange visits to collaborating institutions

We are looking forward to your application with application letter, CV, University degree certificates, and the name and contact details to at least two referees. Your application should be merged into one pdf-file, labelled with your last and first name and sent to application.rockloev@iwr.uni-heidelberg.de until February 28, 2022.

Heidelberg University stands for equal opportunities and diversity. Qualified female candidates are especially invited to apply. Disabled persons will be given preference if they are equally qualified. Information on job advertisements and the collection of personal data is available at www.uni-heidelberg.de/en/job-market