PhD Students (f/m/d) at the Helmholtz School for Integrated Data Science in Environmental and Life Sciences (IDEAS)

What You Can Expect

At IDEAS, you can expect 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

• FloodLens: Develop physically interpretable, robust, and trustworthy data-driven seasonal and sub-seasonal forecasts of spatially co-occurring flood events and their large-scale atmospheric precursors using advanced deep learning architectures and causal representation learning frameworks coupled with explainable AI.
  • Skills Required: Advanced deep learning, causal representation learning, explainable AI, physical interpretation, robustness, trustworthiness, data-driven forecasting, seasonal and sub-seasonal forecasts, spatially co-occurring flood events, large-scale atmospheric precursors.
• SoilCloudAI: Identify soil moisture–cloud feedback pathways from in-situ, satellite, reanalysis, and climate-model data using interpretable and probabilistic graph-based AI methods.
  • Skills Required: Graph-based AI, interpretability, probabilistic modeling, soil moisture, cloud feedback, in-situ, satellite, reanalysis, climate-model data.
• TRACE-GBM: Design novel mini-protein binders against glioblastoma biomarkers using state-of-the-art generative protein design, machine learning, radiochemistry, and PET imaging.
  • Skills Required: Generative protein design, machine learning, radiochemistry, PET imaging, computational design, experimental validation, theranostic applications.
• SafeBEEP: Predict the elimination of plant protection products by the microbiome of pollinators using data science and AI, aiming to keep the bees safe.
  • Skills Required: Data science, AI, microbiome prediction, plant protection products, pollinator microbiome, elimination prediction.
• DigitHealth: Develop novel digital markers of tissue health from continuous metabolic sensing data by combining advanced biosensing technologies with machine learning and data science.
  • Skills Required: Advanced biosensing technologies, machine learning, data science, continuous metabolic sensing, tissue health, digital markers, structured workflow: Generate Data → Expand Biological Measurements → Learn Digital Markers → Predict Outcomes and Support Decisions.

Innovation Track

In addition to the advertised projects, IDEAS offers an Innovation Track for exceptional, self-developed project ideas. Your idea can be shaped freely, but must fall within Life Sciences & Health or Environmental Sciences. Before applying, you must obtain the support of two IDEAS PIs – one from a Helmholtz Center and one from a university (Y-supervision principle).

Hard Facts

• Place of work: Leipzig or Dresden, depending on the project; mobile work possible
• Working time: 100% (39h/week)
• Contract limitations: Limited contract / 3 years (extension by a fourth year is possible)
• Salary: Remuneration according to the TVöD public sector up to pay grade 13 including attractive public-sector social security benefits

Contact

Contact: Sandra Hille (UFZ – Tel.: +49 341 6025 4674) Anne Pidt (HZDR – Tel.: +49 351 260 4716)

Contact Team Recruiting

Email: jobs@hzdr.de

Job Vacancies at the Helmholtz Association

Please find all information on application submission on the IDEAS website.