PhD Students; f/m/d Helmholtz School Integrated Data Science in Environmental and L
Job in
Indiana Borough, Indiana County, Pennsylvania, 15705, USA
Listing for:
Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
Apprenticeship/Internship
position
Listed on 2026-03-01
Job specializations:
-
IT/Tech
Data Scientist, Data Analyst, Data Science Manager
-
Research/Development
Data Scientist
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly
USD
80000.00
100000.00
YEAR
Job Description & How to Apply Below
Position: PhD Students (f/m/d) at the Helmholtz School for Integrated Data Science in Environmental and L[...]
Overview
The Helmholtz School for Integrated Data Science in Environmental and Life Sciences (IDEAS) connects domain-science expertise of UFZ and HZDR with the data/information science strength of Leipzig University (LU) and Dresden University of Technology (TUD), supported by CASUS as an interdisciplinary bridge. IDEAS is part of the Helmholtz Information & Data Science Schools under the Helmholtz Data Science Academy (HIDA).
Our research focus
IDEAS advances and applies modern data science to complex challenges in environmental and life sciences (e.g., machine learning, explainable AI, uncertainty quantification, and AI-ready FAIR data and research data management).
What You Can Expect At IDEAS
IDEAS offers structured, interdisciplinary supervision and training, including joint supervision across disciplines, a Thesis Advisory Committee (TAC), a tailored curriculum, and cohort activities (seminars, hackathons, retreats), plus strong career development and networking through the IDEAS/HIDA ecosystem.
PhD topics
This collective call includes 8 PhD topics, of which 6 positions will be funded. Applicants can be considered for multiple projects and will be matched through a structured selection and ranking process.
Climate Disasters — Climate disasters cause major human and economic losses, but it remains difficult to explain why impacts differ across places and time. This PhD project combines newly available disaster, socio-economic, and satellite datasets with interpretable machine learning to disentangle the roles of hazard intensity, exposure, vulnerability, and environmental conditions. You will develop data-science methods that address biased impact records and the spatio-temporal structure of the data, with the goal of improving our understanding of what drives disaster impacts and making climate-risk assessment more reliable.Beyond Traditional Monitoring — Traditional chemical monitoring can miss short-lived or poorly captured pollution events—yet these may be visible in newspapers, local reports of fish kills, or social-media complaints about odours and discoloured rivers. This PhD project develops AI-based methods to integrate such event signals with regulatory intelligence and chemical data in the SARDINE platform. The aim is to strengthen mixture risk assessment and improve freshwater protection by revealing monitoring blind spots and better characterising real-world exposure.Decoding Protein Darkmatter — Many proteins remain “functionally uncharacterised,” representing a major blind spot in biology and biotechnology. In this PhD project, you will use protein language models trained on billions of sequences to study how scale, and evolutionary and ecological diversity, shape model generalisation. You will develop interpretable and robust embeddings and validate predictions with Helmholtz lab partners, ultimately enabling discovery of novel enzymes relevant for sustainable biotechnology.Estimating LLM Biodiversity — Large language models rely heavily on internalised factual knowledge, but the true extent of that knowledge is hard to measure. This PhD project reframes LLM knowledge as “knowledge diversity,” drawing an analogy to biodiversity in ecology, and applies ecological estimation methods to infer the amount of knowledge from limited samples. By bridging computer science and statistical ecology, the project aims to produce reliable knowledge estimates for LLMs while also stress-testing and advancing biodiversity estimators at scale.AI Against Cancer — This PhD project develops multimodal AI that integrates clinical text and medical imaging to reduce over diagnosis, over treatment, and unnecessary monitoring in prostate cancer—supporting better decisions for thousands of patients. You will combine foundation models and LLM-based agents with large-scale computing in an international team spanning Helmholtz (Germany) and Danish clinical and technical partners, with close day-to-day clinical supervision.
The goal is clinically relevant decision support with direct, measurable patient impact.Inequalities in Climate Discourse — Political attention to climate change and disasters varies…
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