Doctoral; PhD position in “-cycle sustainability assessment of alternative feeds in Europe

School of Agriculture, Policy & Development

Organisation/Company University of Reading Department School of Agriculture, Policy & Development Research Field Agricultural sciences » Zootechnics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Final date to receive applications 1 Mar 2026 - 12:00 (Europe/Brussels) Country United Kingdom Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Jul 2026 Is the job funded through the EU Research Framework Programme?

Horizon Europe - MSCA Marie Curie Grant Agreement Number  Is the Job related to staff position within a Research Infrastructure? No

The Marie Skłodowska-Curie Actions Doctoral Network (MSCA-DN) FEATURE (Future feeds for sustainability in European livestock production) invites applications for one fully funded 36-month full-time PhD position at the University of Reading, United Kingdom
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This doctoral project will contribute to the Life Cycle Sustainability Assessment (LCSA) of integrating alternative feed resources into European livestock systems. The candidate will combine environmental, economic, and social sustainability modelling within a coherent analytical framework, drawing on Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and ecosystem-services valuation. A key component of the research will involve the Optimal Land Use Model (OLUM), a linear-programming-based optimisation model used to evaluate land-use, productivity, and sustainability trade-offs at regional and national scales.

Together, these approaches will allow the DC to investigate how shifts toward novel feed sources influence system-wide performance, emissions, resource use, and wider socio-economic outcomes. Working closely with experimental researchers across the FEATURE network, the successful candidate will synthesise data from livestock trials to assess the implications of incorporating alternative feeds into ruminant, pig and poultry systems. The project will analyse how these feed transitions propagate through supply chains under different socioeconomic and climate scenarios, identifying both potential trade-offs and opportunities for sustainable transformation.

This position offers rich interdisciplinary training in environmental modelling, agricultural systems analysis, and sustainability science, providing an exceptional foundation for a career at the interface of science, policy, and innovation.

It also includes training secondments at the Spanish National Research Council for animal trials and methane measurements and at an industry partner for data collection.

The FEATURE network brings together six academic institutes, five research organisations and seven industry partners across seven European countries. Its 13 doctoral candidates will receive interdisciplinary training in sustainable and circular livestock production, combining animal nutrition, environmental science, data analysis, and socioeconomics. Each candidate will follow a personalised development plan, participate in training schools and workshops, and complete research secondments with industry partners.

The network provides an excellent foundation for future research leaders committed to advancing sustainability, resilience, and innovation in European food systems.

• A strong interest in sustainability modelling and livestock systems
• Experience or interest in LCA, LCC, environmental modelling, or systems analysis
• Competence in data handling and programming/statistical tools (e.g., R, Python)
• Strong analytical, problem-solving, organisational, and communication skills, including excellent written and spoken English
• Ability to work effectively in an interdisciplinary and international research environment
• Motivation to participate actively in training, collaboration, and mobility within the Marie Skłodowska-Curie network

Experience with any of the following is advantageous but not required:

• Life Cycle Assessment (LCA) software/tools
• Geospatial analysis using Geographic Information Systems (GIS)
• Experience with optimisation or economic modelling tools (e.g., GAMS)
• Sustainability indicators and socio‑economic assessment