PhD Position (65%) Combining field observations with remote sensing data in plant phenology research

Friedrich-Schiller-Universität Jena; Remote; EUR 30.000 - 45.000; Teilzeit

Zusammenfassung

A leading research university in Germany is seeking a motivated PhD student for a part-time position in plant phenology research. You'll conduct innovative studies using remote sensing and field observations. Responsibilities include supervising research assistants, publishing findings, and contributing to broader scientific outreach. The ideal candidate should hold a master's degree in ecology or related fields, with strong expertise in remote sensing and statistical analysis. Join a vibrant science community with substantial support and benefits.

Leistungen

Health promotion and sports activities

Family-friendly environment

30 days paid vacation plus additional days

Health insurance

Comprehensive doctoral support

Qualifikationen

• Master’s degree in a relevant field with remote-sensing expertise.
• Strong knowledge of remote-sensing techniques and statistical analysis in R.
• Independent, self-motivated, with excellent communication skills.
• Excellent English language skills.

Aufgaben

• Apply remote-sensing techniques including terrestrial laser scanning.
• Merge and curate phenological data.
• Collect field data on plant phenology.
• Analyze phenological data using statistics and AI methods.
• Supervise student research assistants.
• Publish findings and contribute to outreach activities.
• Work towards completion of a PhD.

Kenntnisse

Remote-sensing techniques

Statistical analysis in R

Handling large data sets

Excellent problem-solving skills

Interpersonal and communication skills

English language proficiency

Ausbildung

Master’s degree in ecology, geography, environmental science, or related field

Jobbeschreibung

PhD Position (65%) – Plant Phenology Research

We are seeking a highly motivated PhD student to conduct cutting‑edge research in plant phenology, combining field observations with remote sensing data, at the Friedrich Schiller University Jena.

Responsibilities

• Apply remote‑sensing techniques, including terrestrial laser scanning
• Merge & curate phenological data from ground‑based observations and remote sensing
• Collect field data on plant phenology and plant traits, including frost‑resistance measurements in the lab
• Analyze phenological data across spatial and temporal scales using advanced statistics and AI methods
• Supervise student research assistants and thesis students
• Publish findings, present at conferences, contribute to outreach activities and teaching
• Work towards completion of a PhD within the project’s research area

Your Profile

• Master’s degree in ecology, geography, environmental science, or a related field with remote‑sensing expertise
• Strong knowledge of remote‑sensing techniques, statistical analysis in R, and handling large data sets
• Independent, self‑motivated, with excellent problem‑solving, interpersonal and communication skills
• Excellent English language skills

Offer

• Integration into a vibrant biodiversity science community, including the Senckenberg Institute for Plant Form and Function and the ELLIS unit
• Close cooperation with MPI‑bgc and other GENAI‑X PhD students
• Comprehensive doctoral support through the Graduate Academy and iDiv network
• A mix of field‑based and computational research with creative freedom
• Health promotion, sports activities, family‑friendly environment, and comprehensive vacation and benefits package (30 days paid vacation, plus two days off on 24th and 31st December, and health insurance)
• Remuneration according to the Collective Agreement for the Public Sector (TV‑L E‑13) with annual payment and fringe benefits

Additional Information

This is a position for a maximum of four years, part‑time (65% — 26 hours per week). Candidates with severe disabilities will be given preference if qualifications are equal.

We look forward to your application by 03.01.2026.

Contact

For further information, contact Christine Römermann ([e-mail]).