Miguel Mahecha

Leipzig University is seeking a postdoctoral researcher to join the Horizon Europe project OASIS, focusing on the intersection of environmental data science, artificial intelligence, and natural language processing. The position is based in the Environmental Data Sciences and Remote Sensing working group at the Institute for Earth System Science and Remote Sensing, under the supervision of Professor Miguel Mahecha and Dr Guido Kraemer. The OASIS project aims to develop AI-powered methods and interfaces for working with environmental and geospatial data, supporting research on climate, biodiversity, and water systems. The successful candidate will conduct high-quality research at the interface between natural language, environmental data, and domain-specific process models. Responsibilities include implementing Model Context Protocol (MCP) servers, developing chat interfaces, collaborating with international partners, and contributing to scientific publications and project dissemination. Applicants should hold a doctorate in computer science, remote sensing, data science, ecology, environmental sciences, geography, hydrology, or a related field. Strong programming skills in Python, R, or similar languages, and experience with large language models, APIs, and natural language interfaces are advantageous. Excellent English communication skills and the ability to work in an international consortium are required. Experience in stakeholder engagement is desirable. The position is fully funded through the Horizon Europe project, with remuneration according to salary group 13 TV-L. The contract is fixed-term until 30 April 2030, with benefits including annual bonus, company pension plan, flexible working hours, professional development opportunities, and discounted public transport. Leipzig University encourages applications from women and individuals with disabilities. For more information and to apply, visit the official job posting. For accessibility assistance, contact the university's disability officers at schwerbehindertenvertretung@uni-leipzig.de.

Leipzig University is advertising a postdoc position in LLM/NLP, environmental data science, remote sensing, and Earth system science . The role sits in the Institute for Earth System Science and Remote Sensing at the Faculty of Physics and Earth System Science, within the Environmental Data Sciences and Remote Sensing working group led by Professor Miguel Mahecha and Dr Guido Kraemer , with collaboration also mentioned with Johannes Quaas . The project is part of the Horizon Europe initiative OASIS (“Observation and AI-powered System for Intelligent water Solutions”), aiming to deliver Earth Intelligence for biodiversity , climate change , water cycle management , resilience, and policy support. The postdoc will work at the interface of natural language interfaces , environmental data , and domain-specific process models to create factually trustworthy, policy-relevant outputs. Key tasks include implementing Model Context Protocol (MCP) servers , developing chat interfaces, supporting project partners with natural language tools for analysing environmental data, coordinating technical implementation across international partners, and contributing to publications, reports, workshops, and stakeholder engagement. The post is especially relevant for candidates with strong programming skills and experience with Python , R , LLMs , APIs, agents, and open-source or portfolio-based evidence of technical work. Eligibility highlights: a completed doctorate in computer science, remote sensing, data science, ecology, environmental sciences, geography, hydrology, or a related field; excellent English; and the ability to work in an international consortium. The position is 100% funded , fixed-term, and expected to run until 30 April 2030 , with salary at TV-L E13 . The post mentions flexible working, professional development, and a supportive university environment. Application is via the Leipzig University job portal linked in the post. The post does not state a separate deadline in the text provided.