Research Associate – Land Systems Science

Minor Hotels Europe and Americas

. Work with Prof Marion Pfeifer and international research partners on the five-year TIF-CER ERC project .

Posted 10/28/2026full-timeNewcastle • United KingdomJuniorMid-Level💰 £37,369 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in mechanistic modelling and hydrological processes, with a strong ability to integrate spatial and temporal datasets. Proven experience in field research design, collaboration across disciplines, and effective communication through publications and presentations.

Highest-signal resume keywords

PhD In GeomorphologyMechanistic ModellingHydrological ProcessesField Research DesignData Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Quantitative ModellingStatistical ModellingSpatial ModellingData IntegrationField Data CollectionRemote SensingEcosystem Services AnalysisFlood Risk AssessmentDrought Risk AssessmentResearch Dissemination

Soft Skills

CollaborationCommunicationTrainingCommitment To Professional DevelopmentAbility To Meet Deadlines

Tools & Technologies

Hydrological ModelsLand-System ModelsOffice ApplicationsRemote Sensing ToolsData Analysis Software

Industry Keywords

Environmental ScienceLand Systems ScienceBiodiversityEcologyTropical Landscapes

Tech Stack

Tools & technologies

Remote Sensing

About the role

Key responsibilities & impact

Work with Prof Marion Pfeifer and international research partners on the five-year TIF-CER ERC project
Quantify climate and biodiversity functions and associated ecosystem services and disservices of tree-based agricultural systems
Focus on hydrological processes, water use, flood and drought risks at tree, farm and catchment scales
Develop and apply mechanistic models
Integrate field observations, remote sensing and spatial datasets with hydrological and land-system models
Design and implement standardised field data collection across the international TIF-CER network
Train research assistants and local research teams in standardised data collection
Collaborate with ecologists, biodiversity scientists, social scientists and local stakeholders
Contribute to co-designed scenario modelling and decision-support tools
Contribute to research dissemination through seminars, conferences and publications
Contribute to grant applications and develop research objectives and funding proposals
Co-supervise two PhD students
Undertake substantial international travel, particularly during project years 1 and 2

Requirements

What you’ll need

PhD in geomorphology, hydrology, remote sensing, land systems science, environmental science or a closely related discipline
Extensive applied experience using mechanistic modelling approaches to investigate hydrological processes and/or flood and drought risks at catchment scales
Knowledge and experience of land systems science, geomorphology, hydrology and/or remote sensing
Ability to integrate spatial and temporal environmental datasets
Experience working across disciplinary boundaries, particularly with ecologists and/or biodiversity scientists
Experience designing and implementing field research in rural and/or tropical landscapes
Experience working with local research teams and stakeholders to co-design research processes and outcomes
Excellent quantitative modelling and data analysis skills
Experience applying statistical and/or spatial modelling approaches to environmental datasets
Proven ability to analyse data and write up results
Excellent IT skills in all major office applications
Experience presenting at conferences and/or publishing in high-quality outlets
Ability to work collaboratively and meet deadlines
Commitment to continued professional development
Understanding of good practice in equality, inclusion and diversity

Benefits

Comp & perks

Generous holiday package
Opportunity to buy additional holiday
Great pension schemes
Health and wellbeing initiatives
Career development support for research colleagues
Equal opportunities and inclusive workplace
Disability Confident employer interview scheme for disabled applicants meeting essential criteria