PostDoc in Computational Ecology (m/f/x)

Institution Faculty of Biology - Zelluläre und Organismische Netzwerke 
Remuneration group TV-L E13 
Full-time / Part-time Vollzeit oder Teilzeit 
Start date Early 2025, for 3 years 
Application deadline 2024-10-13

About us:

Are you passionate about biodiversity, ecological communities, and species interactions? Do you enjoy data wrangling, coding, and analysis? If so, we may have an exciting opportunity for you.

Our research focuses on the diversity, dynamics, coevolution, and processes within species interaction networks, particularly - but not exclusively - involving the pollinator-microbe-plant triangle. Both positions will engage in computational research, including statistical modeling, bioinformatics processing, tool development, meta-analyses, and deep learning in the context of biodiversity and ecological interaction networks (bi- and multipartite), utilizing both molecular and classic ecological datasets. Current topics in our group include ecological network resilience, land-use gradients, climatic niches, microbiome assembly and function, pipeline development in AI-based image and sequence analyses.

We are looking for you:

PostDoc in Computational Ecology (m/f/x)

in Planegg-Martinsried

Your tasks and responsibilities:

We have a wealth of exciting datasets at our disposal, focusing on networks (e.g., metabarcoding, metagenomics, observations), ecological traits, bacterial genomes, and community monitoring data (e.g., eDNA, occurrences, video, and photos). These data come from diverse ecosystems, environmental gradients, and experimental designs, offering unique opportunities for meta- or in-depth data analysis for this position. The role will involve:

• developing research questions using ecological theory
• analyzing data
• developing and testing new methods
• sharing scientific results
• teaching responsibilities (5 SWS) and supervising thesis students
• potential third-party funding applications
• coordination

Your qualifications:

• Strong interest in computational ecology, biodiversity and interaction ecology as well as ecological theory
• Interest and/or experience in analysis of big and heterogeneous datasets. Previous knowledge on data synthesis, metabarcoding, phylogeny, bioinformatics and deep-learning are of benefit
• Routine with coding in R and/or Python
• PhD in natural sciences or equivalent, particularly in the areas of ecology or bioinformatics with focus on computational analyses in the dissertation
• High motivation for a career in science
• Willingness and aptitude for self-responsible and independent work
• Good writing, reading and communication skills in English

Benefits:

Salary and benefits are according to public service positions in Germany (TV-L). Our research group (Cellular and Organismic Networks) offers a friendly and stimulating working atmosphere in an international team and strong support for your career. The group is integrated into various coordinated research endeavors, which can serve as a basis to build up an own research network. Our lab is equipped with state-of-the-art tools and techniques. We are part of the HighTechCampus Planegg-Martinsried at one of the largest German universities. A balanced work-life relationship is important to us, we offer options to make this position also as a part time contract, flexible working times or with part time remote home-office. The LMU signed the "Charta of Diversity" and advocates gender and background equality. Women and minorities are therefore strongly encouraged to apply.

In addition, you can benefit from the various LMU corporate benefits

People with disabilities who are equally as qualified as other applicants will receive preferential treatment.

Contact:

Please send your application as one single pdf file per email to Prof. Alexander Keller until 13. October 2024. Applications should include a cover letter, a short summary of research interests, CV including publications and third-party funding, and names (with email addresses) of two potential referees.

Please let us know briefly in your cover letter through which medium/website/etc. you became aware of our job advertisement.

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