The Animal Nutrition Group at ETH Zürich, led by Professor Mutian Niu, is seeking a talented Postdoctoral Researcher or experienced Data Scientist to join their interdisciplinary team. This position centers on leveraging advanced data science, machine learning, and AI methodologies to address critical challenges in sustainable livestock production, with a particular focus on dairy cattle nutrition. The group integrates hypothesis-driven experiments and data-driven approaches to enhance nutrient utilization efficiency in ruminants, aiming to optimize production efficiency, animal health, and environmental impact.

Key research areas include feed and feeding strategies, nutritional physiology, precision livestock farming, and multi-omics approaches for sustainable dairy farming. The successful candidate will design and implement statistical and machine learning models to analyze large-scale datasets encompassing metabolomics, microbiomics, animal behavior, and production performance. Responsibilities also involve integrating multi-omics data with environmental and production metrics, applying emerging methodologies such as causal inference, and collaborating with experimental biologists to validate models and translate insights into practical recommendations for sustainable farming.

The position offers flexibility to align with the candidate’s expertise, bridging computational innovation with biological applications in animal nutrition. For PhD holders, there are opportunities for independent research projects and mentoring junior team members; experienced data scientists may focus on applied analytics within ongoing group initiatives. The role includes contributing to grant proposals, publications in high-impact journals, and open-source tool development.

Applicants should possess a PhD in data science, computer science, applied mathematics, bioinformatics, statistics, animal science, or a related field. Candidates with a Master’s degree and at least three years of relevant professional experience are also eligible. Essential skills include expertise in statistical modeling, machine learning (supervised/unsupervised learning, deep learning), and AI frameworks (Python, R, TensorFlow, PyTorch). Experience with biological or animal science data, such as omics or time-series production data, is highly desirable. Familiarity with ruminant nutrition, sustainability modeling, or precision agriculture is a plus. Proficiency in data handling, visualization, and high-performance computing is expected, along with excellent communication skills and fluency in English.

ETH Zürich offers a stimulating research environment with access to state-of-the-art facilities and datasets, professional growth opportunities including conferences and industry collaborations, and a competitive salary in accordance with ETH Zurich standards. The institution values diversity, sustainability, and an inclusive culture, supporting work-life balance and fostering an environment where all staff and students can thrive.

Applications are accepted online and reviewed on a rolling basis, with a preferred start date in early 2026. Interested candidates should submit a cover letter, detailed CV with publication list, contact details for 2-3 professional references, and optionally a GitHub portfolio or examples of data science projects. For questions about the position, contact Professor Mutian Niu at [email protected] (no applications via email).

ETH Zürich is recognized globally for excellence in science and technology, offering a vibrant, international community dedicated to solving global challenges in food security and environmental sustainability.