The IBB offers two JAE-Intro fellowships for undergraduate and master’s students interested in research
The call was published in the Spanish Official Gazette (BOE) on 11 March 2026 and offers students the opportunity to carry out a research placement in one of the institute’s research groups in cutting-edge fields such as evolutionary genomics, biodiversity, and artificial intelligence applied to ecological data.
AVAILABLE POSITIONS
The Botanical Institute of Barcelona offers two JAE-Intro fellowships in the following research projects:
- Transposable elements in transcriptome diversification
- Artificial intelligence to enhance the scientific value of citizen science biodiversity data
POSITION 1 · TRANSPOSEABLE ELEMENTS IN TRANSCRIPTOME DIVERSIFICATION
Transcriptomes are dynamic systems in which different cells, tissues, or body parts express specific sets of transcripts. Transposable elements (TEs) are an important source of transcriptome diversity; however, many studies focus on specific types of chimeric transcripts, single tissues, or incomplete TE annotations.
This project is developing a computational tool to automatically and comprehensively identify gene-TE chimeras. The selected student will contribute to improving and applying this tool to different species across the tree of life, helping to better understand the role of transposable elements in genome evolution.
Training and activities
- Development of computational pipelines.
- Use of high-performance computing (HPC).
- Training in genetics, evolution, and transposable elements.
- Improvement of scientific writing and presentation skills.
- Participation in research group meetings and institute seminars.
Principal investigator: Josefa González
Contact: josefa.gonzalez@csic.es
Position code: JAEINT26_EX_0528
POSITION 2 · ARTIFICIAL INTELLIGENCE TO ENHANCE THE SCIENTIFIC VALUE OF CITIZEN SCIENCE BIODIVERSITY DATA
Citizen science data have increased exponentially in recent years and have become a key source of information for studying the recent distribution of species. However, these datasets present important limitations, such as taxonomic and geographic biases, heterogeneous data quality, and uneven spatial coverage.
This project explores how artificial intelligence and machine learning algorithms can help address these limitations by detecting ecological patterns, identifying knowledge gaps, and proposing more informative sampling strategies.
Training and activities
- Data identification and harmonization: selection of citizen science data sources and application of automated filtering and quality control techniques.
- AI-based analysis workflows: development of scripts in R to work with large volumes of GBIF data using machine learning algorithms such as decision trees, random forests, and clustering methods.
- Advanced analysis and sampling optimisation: evaluation of the information provided by citizen science data and exploration of sampling strategies based on model uncertainty and active learning approaches.
The selected student will also participate in scientific meetings and interactions with national and international research teams.
Principal investigator: Pep Serra
Contact: pep.serra.diaz@csic.es
Position code: JAEINT26_EX_0365
GENERAL INFORMATION ABOUT JAE-INTRO FELLOWSHIPS
JAE-Intro fellowships are research initiation grants aimed at undergraduate and official master’s students interested in gaining experience in scientific research.
- Duration: 7 consecutive months.
- Mode: on-site.
- Dedication: 20 hours per week.
- Funding: €4,200 total per fellowship (€600 per month).
APPLICATION PROCEDURE
- The call was published in the BOE on 11 March 2026.
- Application deadline: 11 April 2026.
- Applications must be submitted through the CSIC online application system.
- Contact: jae@csic.es