Publisher
source

Mutian Niu

4 months ago

Postdoctoral Position/Data Scientist in Animal Nutrition ETH Zürich in Switzerland

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Switzerland

University

ETH Zürich

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Where to contact

Official Email

Keywords

Computer Science
Data Science
Microbiology
Environmental Science
Agriculture
Biology
Nutrition
Artificial Intelligence
Computational Biology
Animal Nutrition
Livestock Management
Environmental Sustainability
Omics
Nutritional Biochemistry
Statistical Modelling
Bioinformatic
Cattle
Statistic
Metabolomic
Machine learning

About this position

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].

Funding details

Available

What's required

Applicants should hold 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 3 years of relevant professional experience will also be considered. Required skills include strong 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 (omics, 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 (Python/R for analysis, cloud computing) is expected. Excellent communication skills, a collaborative mindset, and fluency in English (written and spoken) are required.

How to apply

Submit your application via the ETH Zurich online application system. Include a cover letter, detailed CV with publication list, and contact details for 2-3 professional references. Optionally, provide a GitHub portfolio or examples of data science projects. Applications are reviewed on a rolling basis.

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