ETH Zürich's Animal Nutrition group, led by Assistant Professor Mutian Niu, is recruiting a PhD student for a cutting-edge project in dairy cattle physiology and health. The research focuses on metabolic discovery and mechanistic physiology using exhalomics (exhaled breath metabolomics) to advance sustainability in dairy farming. The successful candidate will work at the interface of ruminant nutrition, animal health, and physiological phenotyping, integrating animal experiments with advanced analytical techniques and bioinformatics. The project includes three main components: (1) controlled nutritional experiments to study dietary impacts on rumen function and metabolism, (2) immune challenge experiments to investigate inflammatory states and metabolic signatures, and (3) large-scale exhalomics comparing healthy and hospitalized animals. The work involves in vivo and in vitro experiments, physiological and metabolic sampling (rumen, breath, blood, fecal, urine, milk), and high-resolution mass spectrometry data analysis. Collaboration with world-leading researchers from Iowa State University, PSI Paul Scherrer Institut, and University of Zurich is part of the program. Applicants should have a Master's degree in Animal Science, Biology, Physiology, Veterinary Science, Biochemistry, Bioinformatics, or related fields. Essential skills include experimental work, motivation for animal research, scientific curiosity, teamwork, and English proficiency. Experience in metabolomics, mass spectrometry, nutritional or immunological models, analytical chemistry, and data science/bioinformatics is advantageous. ETH Zürich offers a stimulating research environment, competitive salary, flexible working hours, and support for work-life balance. The university values diversity, inclusion, and sustainability. Application evaluation and interviews start January 5, 2026, with a preferred start date in Spring 2026. To apply, submit a cover letter, CV with publication list, transcripts, Master thesis (if available), and contact details for 2-3 professional references via the ETH Zurich online application system. For questions, contact Mutian Niu at [email protected] (no applications by email). Keywords: Animal Nutrition, Dairy Cattle Physiology, Metabolomics, Exhalomics, Ruminant Nutrition, Animal Health, Physiological Phenotyping, Mass Spectrometry, Bioinformatics, Sustainability.

The Animal Nutrition Group at ETH Zurich, led by Professor Mutian Niu, is seeking a talented Postdoctoral Researcher or experienced Data Scientist to join their interdisciplinary team. The group focuses on advancing sustainable livestock production through innovative nutritional strategies, integrating hypothesis-driven experiments with data-driven approaches to enhance nutrient utilization efficiency in ruminants, particularly dairy cattle. The successful candidate will harness AI, machine learning, and statistical modeling to analyze cutting-edge datasets in precision feeding, animal behavior and welfare, multi-omics, and environmental impact. Key responsibilities include designing and implementing statistical and machine learning models for nutrient metabolism, rumen function, physiological responses, and feed efficiency; integrating multi-omics data with environmental and production metrics to support precision farm management strategies; leveraging emerging methodologies such as causal inference to uncover complex biological functions; collaborating with experimental biologists to validate models and translate insights into practical recommendations for sustainable farming; and contributing to grant proposals, publications, and open-source tool development. The position offers flexibility to align with the candidate's expertise, bridging computational innovation with biological applications in animal nutrition. Applicants should have a PhD in data science, computer science, applied mathematics, bioinformatics, statistics, animal science, or a related field, or a Master's degree with at least three years of relevant professional experience. Strong expertise in statistical modeling, machine learning, and AI frameworks (Python, R, TensorFlow, PyTorch) is required, along with experience in handling biological or animal science data. Familiarity with ruminant nutrition, sustainability modeling, or precision agriculture is a plus. The group values excellent communication skills, a collaborative mindset, and fluency in English. ETH Zurich offers a stimulating research environment, access to state-of-the-art facilities and datasets, professional growth opportunities, competitive salary, flexible working hours, and support for work-life balance. The university is committed to diversity, inclusion, and sustainability. Applications are accepted online and reviewed on a rolling basis, with a preferred start date in early 2026. For questions about the position, contact Professor Mutian Niu at [email protected].

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.