PhD Candidate in Response Diversity and Climate Resilience

Centro de Investigaciones sobre Desertificación (CIDE, CSIC-UV-GVA); España; Sur place; EUR 29 000 - 36 000; Plein temps

Avantages offerts par ce poste

Relocation support

Résumé du poste

The Centro de Investigaciones sobre Desertificación (CIDE), in collaboration with the University of Valencia, invites applications for a Doctoral Candidate position within the ReDiLEEP MSCA Doctoral Network. The project investigates response diversity through trait-based ecology using regional and global vegetation data.

The successful candidate will address how climatic extremes affect ecosystem stability, combining observational and experimental approaches with interdisciplinary training and

Qualifications

• Master's degree in Ecology, Environmental Sciences, or related disciplines.
• Strong interest in community ecology, biodiversity and ecosystem functioning.
• Experience with ecological experiments and/or quantitative data analysis.
• Strong data analysis skills (preferably in R).

Responsabilités

• Create a Personal Career Development Plan outlining objectives, timelines, and skills.
• Design and conduct lab microcosm experiments to study how drivers affect species responses and ecosystem stability.
• Analyze experimental and field data using advanced statistics.
• Communicate results to ReDiLEEP predictive-model developers.
• Publish in journals and present at international conferences.
• Participate in ReDiLEEP training, secondments, dissemination, and reporting.

Connaissances

Interest in community ecology

Ecological experiments

Quantitative data analysis

Data analysis in R

Formation

Master's degree in Ecology, Environmental Sciences, or related disciplines

Outils

R

Description du poste

The Centro de Investigaciones sobre Desertificación (CIDE), in collaboration with the University of Valencia, invites applications for a Doctoral Candidate position within the ReDiLEEP MSCA Doctoral Network. The project investigates response diversity through trait-based ecology using regional and global vegetation data.

The successful candidate will address how climatic extremes affect ecosystem stability, combining observational and experimental approaches with interdisciplinary training and