PhD Student in AI-Driven Digital Phenotyping and Genomics: Decoding Evolutionary Morphology in Domesticated Animals Swedish University of Agricultural Sciences in Sweden

The Department of Animal Biosciences at the Swedish University of Agricultural Sciences (SLU) in Uppsala is offering a fully funded PhD position in the field of AI-driven digital phenotyping and genomics, focusing on evolutionary morphology in domesticated animals. This opportunity is part of the Data-Driven Life Science (DDLS) program, which aims to train the next generation of computational biologists and build internationally leading capabilities in Sweden.

The doctoral project, titled "The code that shapes the body: AI and digital phenotyping to decode evolutionary morphology in domesticated animals," seeks to uncover how genetic variation influences body form and function. The research will develop a data-driven framework linking DNA, 3D body shape, and motion in horses, leveraging multimodal datasets such as images, 3D models, breeding assessments, motion data, and whole-genome sequences.

The PhD student will work on three interconnected research directions: multimodal modelling integrating language, visual, and quantitative shape representations; analysis of structure–function relationships between morphology and movement; and modelling genome–phenotype relationships using machine learning and genomic language models. The project offers a unique interdisciplinary environment at the interface of artificial intelligence and biology, combining computer vision, machine learning, genomics, and biomechanics.

Supervision will be provided by Associate Professor Elin Hernlund (SLU), Professor Hedvig Kjellström (KTH Royal Institute of Technology), and Associate Professor Sofia Mikko (SLU), with additional collaboration from international partners at the Max Planck Institute for Intelligent Systems, IMATI-CNR, and Parma University. The supervisory team brings expertise in computer vision, machine learning, and genomics, ensuring strong interdisciplinary training and access to advanced infrastructure including 3D scanning systems, motion capture technologies, and high-performance computing resources.

The position is based at SLU’s Department of Animal Biosciences, within the Animal Locomotion and Emotion Laboratory, and is part of the Faculty of Veterinary Medicine and Animal Science. The department covers a wide range of research areas, from molecular mechanisms and microbiology to animal structure, function, and behavior, with a focus on how these are affected by genetics, breeding, physical activity, care, production, stress, environmental factors, and diseases.

Applicants must have a Master’s degree or equivalent, with at least 240 credits (60 at second-cycle level), and at least 90 credits in technology-relevant courses (30 at advanced level). English proficiency equivalent to Swedish upper-secondary qualification Engelska B/6 is required. Candidates should have experience in programming (Python preferred), data science, computer science or biostatistics, and the ability to work independently and collaboratively. Meritorious qualifications include experience with machine learning, deep learning, computer vision, image analysis, 3D data, geometric representations, genetics or biological data, large datasets, or high-performance computing. Analytical ability, curiosity, and interdisciplinary collaboration are highly valued. An interest in animals is a plus.

The PhD student will participate in the DDLS Research School, which offers courses, workshops, and national collaborations. The position is full-time, with a fixed salary progression according to the local collective agreement, and is limited to four years. The start date is October 2026, and the application deadline is 1 June 2026. Selection is based on eligibility and the documents attached to the application.

For more information about staff benefits and doctoral education at SLU, visit the provided links. Applications should be submitted via the application portal, ensuring all required attachments are included. Reference number: SLU.ua.2026.2.5.1-1309.