Phd Student

Mapping Biodiversity Using Data-Driven Methods in Combination with Citizen Science Audio Recordings and Satellite Imagery

**Organisationseinheit**:
Institut für Photogrammetrie und Fernerkundung (IPF)

**Ihre Aufgaben**:
We are seeking a PhD student to investigate data-driven biodiversity classification in a stakeholder process, particularly how audio recordings from citizen scientists and satellite imagery can be integrated to map biodiversity at scale. You will be part of the BMBF-funded project “BiodivKI-2: Biodiversity Assessment of Habitat Types Using Machine Learning Based on Citizen Science Audio Recordings and Satellite Imagery” (Bio-O-Ton-2). Our overarching goal is to develop and test novel machine-learning approaches for combining acoustic and geospatial data, culminating in an interactive platform to support environmental authorities.

Special focus will be on the following key questions:

- How can acoustic data and satellite imagery be combined to classify biodiversity efficiently?
- Which habitat types can be reliably differentiated using this approach?
- How can end-users (e.g., conservation authorities) benefit from a large-scale, cost-effective classification system?

In this role, you will:

- Coordinate and refine data collection from multiple citizen-science platforms.
- Develop automated pipelines (Python-based) for cleaning, merging, formatting and visualizing/interacting with big acoustic and satellite datasets.
- Collaborate with AI specialists to train and validate deep-learning models for biodiversity classification.
- Participate in field campaigns to gather additional ground-truth sound recordings.
- Contribute to co-creation workshops with stakeholders (environmental authorities, NGOs) to align methods with real-world needs.
- Present your work at academic conferences and co-author peer-reviewed publications.

**Eintrittstermin**:
as soon as possible

**Ihre Qualifikation**:
You must hold a Master’s degree in a relevant field (e.g., Geoinformatics, Geoecology, Computer Science, Biology, Biophysics, Environmental Science, Spatial Planning or others) but no PhD. German language skills are beneficial; English proficiency is expected. We welcome applicants who are analytical, creative, and eager to work in an interdisciplinary team.

Beneficial experience and qualities include:

- Interest and/or experience in biodiversity topics, soundscape ecology, or environmental monitoring
- Experience with geospatial data science, machine-learning libraries (e.g., TensorFlow, PyTorch), or data-visualization tools
- (Willingness to acquire) skills in Python (or similar, e.g. R/MATLAB) and web-based interactive mapping (e.g., Python Shiny)
- Familiarity with remote-sensing techniques and data (e.g., Sentinel, PlanetScope)
- Enthusiasm for transdisciplinary research and stakeholder engagement

**Das bieten wir Ihnen**:
Become a member of staff of the only German University of Excellence that conducts largescale research on the national level. Work under excellent working conditions in an international environment and be active in research and academic education for our future. Benefit from specific training when starting your job and from a wide range of further qualification offers. Use our flexible working time models (flexitime, work from home), our sports and leisure offers, as well as our child and holiday care services. We also pay a share of EUR 25/month in the Job Ticket Baden-Württemberg. Enjoy a large variety of dishes, snacks, and beverages at our canteens.

**Salary**:
Salary category 13 TV-L, depending on the fulfillment of professional and personal requirements.

**Contract duration**:
limited for 3 years

**Application up to**:
February 18, 2025

**Contact person in line-management**:
For further information, please contact Dr. Susanne Benz.

**Ausschreibungsnummer: 1051/2025**

Wir streben eine möglichst gleichmäßige Besetzung der Arbeitsplätze mit Beschäftigten (w/m/d) an und würden uns daher insbesondere über Bewerbungen von Frauen freuen. Bei gleicher Eignung werden anerkannt schwerbehinderte Menschen bevorzugt berücksichtigt.
** Kontakt**:
**Bei allgemeinen Fragen zur Bewerbung**:
Personalservice (PSE) - Personalbetreuung
Frau Kehrer
Telefon: 0721 608-45415,

Kaiserstr. 12, 76131 Karlsruhe