Postdoctoral scholarship (2 years) within AI-driven plant genomics
The Department of Plant Physiology is offering a postdoctoral scholarship within the project of AI-driven plant genomics. The scholarship is full-time for two years with access during the fall of 2025 or according to agreement.
Umeå Plant Science Centre (UPSC) is one of the strongest research environments for basic plant research in Europe. Research at UPSC covers a wide range of disciplines in plant biology including ecology, computational biology, genetics, physiology, biochemistry, cell biology and molecular biology (see www.upsc.se). The postdoctoral scholarship holder will be placed at the Department of Plant Physiology which is a part of Umeå Plant Science Centre.
The research group of Jian-Feng Mao is seeking a highly motivated postdoctoral fellow for a two-year fellowship in Artificial Intelligence (AI) driven plant genomics. The project focuses on generating new AI-driven method for identification, annotation and functional investigation of long non-coding RNA (lncRNA) genes in plant genomes.
The Knut and Alice Wallenberg foundation (KAW) funds this two-year postdoctoral scholarship. The scholarship amounts to 348 000 SEK per year and is not subject to tax. The PI covers running costs for the project.
Project description
What if we could decode the hidden language within plant genomes that controls their resilience to climate change, their growth patterns, and their ability to feed our growing population? Beyond the protein-coding genes we've traditionally studied lies an unexplored frontier of long non-coding RNAs (lncRNAs) – mysterious genetic elements that don't create proteins but profoundly influence how plants develop and respond to their environment. Our research group has pioneered computational tools to identify these genetic elements, but we're now ready to make a quantum leap forward using the revolutionary power of artificial intelligence.
Artificial intelligence is transforming the landscape of biological research. While traditional bioinformatics methods have made significant strides, AI approaches - particularly deep learning - are revealing patterns and relationships in biological data that were previously inaccessible.
As a postdoctoral scholarship holder in this project, you'll be at the cutting edge of merging AI with plant genomics. You'll have the opportunity to develop innovative deep learning approaches that can recognize patterns in genetic data beyond human perception, transforming how we identify and understand the function of lncRNAs across diverse plant species.
The postdoctoral scholarship holder will have the opportunity to gain experience in project design, analyses, interpretation and scientific publication and be involved in a project that develops future AI tools for genomic analysis.
Examples of areas in which the scholarship holder will have the opportunity to gain qualifications are:
Data collection and curation. Whole genome sequence and annotation (coding and non-coding) from diverse plant species have been prepared, while curation not.
The development of a classification platform of plant lncRNA. This is will be important for the transfer functional knowledge among species, and to investigate sequence variation, origin and evolution, and further to modelling.
Investigating transcriptional profile of lncRNA. It can be expression quantification, alternative splicing, start sites properties.
Performing AI modeling and developing a new method for lncRNA gene identification from whole genome sequences.
Collaborating with experimental researchers to integrate computational findings/tools with functional investigation.
Scientific communication by contributing to scientific group meetings, collaborations, and publications.
At Umeå Plant Science Centre (UPSC) you will join a vibrant, international community where creativity and scientific curiosity flourish. Our interdisciplinary environment brings together plant biologists, genomics experts, and computational scientists in a collaborative setting that sparks innovation. The postdoctoral scholarship offers access to cutting-edge computational resources from National Academic Infrastructure for Supercomputing in Sweden (NAISS), a wealth of genomic data, and the freedom to pursue ambitious research questions.
This postdoctoral scholarship offers the opportunity to be a part of this AI revolution by developing novel neural network architectures specifically optimized for plant genomic data. Our innovations could become foundational tools used by plant scientists worldwide, advancing our understanding of plant biology and contributing to solutions for global challenges like climate change and food security.
As a postdoctoral scholarship holder, you’ll be involved in building upon our lab's established computational frameworks — Plant-LncPipe, PlantLncBoost, and Plant-LncRNA-pipeline-v2 — to develop new methods incorporating transformer models, graph neural networks, and self-supervised learning approaches that can extract deeper biological insights from genomic data.
Join us in this exciting frontier where artificial intelligence meets plant genomics and help write the next chapter in our understanding of the plant genome's hidden potential.
Qualifications
To qualify as a postdoctoral scholarship holder, the postdoctoral fellow is required to have completed a doctoral degree or a foreign degree deemed equivalent to a doctoral degree. This qualification requirement must be fulfilled no later than at the time of the decision about scholarship recipient.
Priority should be given to candidates who completed their doctoral degree, according to what is stipulated in the paragraph above, no later than three years prior. If there are special reasons, candidates who completed their doctoral degree before that may also be eligible. Special reasons include absence due to illness, parental leave or clinical service, appointments of trust in trade union organizations, or similar circumstances.
Doctoral degree should be within bioinformatics, machine-learning, computational biology, genomics, or a related field, with a focus on computing or data science.
Additional requirements are:
Significant experience in bioinformatics, genomics, computing, machine-learning, or other data science area.
Demonstrated skills in Python programming, or other computer programming.
Strong interest in data science, such data collection and curation, modelling.
Excellent written and oral English communication skills.
Possess the ability to independently further their insight into the research question.
To be able to develop within the research group, the ability to set up and maintain joint schedules is necessary.
Experience in the intersection of deep learning and bioinformatics, especially DNA or protein sequence modeling, is particularly meriting.
Application
The application should be written in English or Swedish, and attached documents should be in Word or PDF format. The application should be registered via Umeå University’s e-recruitment system Varbi and submitted by the deadline September 1, 2025.
A full application should include:
Cover letter highlighting qualification and motivation (max 2 pages)
Curriculum vitae (CV) with publication list,
Verified copy of doctoral degree certificate or documentation that clarifies when the degree of doctor is expected to be obtained,
Verified copies of other diplomas, list of completed academic courses and grades,
Copy of doctoral thesis and relevant articles,
Other documents that the applicant wishes to claim.
Contact information to two persons willing to act as references
Further information
Jian-Feng Mao, Department of Plant Physiology, e-mail: jianfeng.mao@umu.se
