Research Assistant - Still Waters Project

Aberystwyth University; Aberystwyth; Hybrid; GBP 28,000 - 34,000; Full time

Benefits offered by this job

Flexible working policy

Hybrid Working

36.5-hour week

Generous leave entitlements

Job summary

Aberystwyth University invites applications for a Research Assistant to support the Still Waters project, using hydrological models to improve malaria transmission estimates. The role focuses on training data creation, DL pipelines, and malaria habitat mapping from satellite imagery.

You will collaborate with Earth Observation group colleagues and hydrologists at Leeds University, contributing to publications and delivering rigorous validation of maps and methods.

Qualifications

• Experience in Python programming.
• Experience in using cloud-based services like Google Earth Engine and Google Colabs.
• MSc (or equivalent experience) in GIS and remote sensing.
• Working knowledge of GIS platforms, like QGIS.
• An understanding of different approaches to satellite image classification and validation.

Responsibilities

• Develop a comprehensive training data set (i.e. annotated satellite imagery) representing target malaria aquatic habitat types (notably, river corridors).
• Deploy the training data set within Deep Learning pipelines developed by the Earth Observation research group (organised as code blocks within a Python notebook).
• Evaluate the output maps both as an iterative process to determine changes in the Deep Learning pipeline, and as a formal validation of final maps.
• Deploy the final model to produce malaria habitat maps.
• Assist in writing an academic paper to publish the methods and findings of this work.
• Collation of existing datasets on malaria habitat location.
• Develop composites of satellite imagery (likely PlanetScope imagery).
• Manually digitise satellite imagery with known malaria habitats within a GIS environment.
• Modify Python notebook to read and process the training dataset and satellite image composites within an established Deep Learning pipeline.
• Monitor outputs, alongside project partners, to determine modifications of the pipeline to improve the model.
• Validate the final model and final output map.
• Collate details of the approach and findings to present to the wider project team.
• Contribute to a publication reporting the approach and findings.

Skills

Python programming

Google Earth Engine

Google Colabs

GIS

QGIS

Satellite image classification

Education

MSc in GIS and remote sensing

Tools

Google Earth Engine

Python notebook

Job description

This role contributes to the collaborative research project Still Waters: using hydrological models to improve malaria transmission estimates. With a focus on the Zambezi Catchment, this exciting research programme will deploy state-of-the art hydrological models to predict surface water dynamics. These surface water bodies represent potential breeding habitats for malarial mosquitoes. This new data will be used to drive established malaria transmission models to predict the impact of current and future hydrological dynamics on malaria burden at a catchment-wide scale. A key part of this programme is the use of satellite Earth Observation to generate maps of potential malaria habitats to help calibrate and validate hydrological modelling outputs. This will be achieved using sophisticated machine learning and Deep Learning image analysis approaches.

This research assistant will train, deploy and evaluate Deep Learning models to predict the location of malaria habitats using satellite imagery. These activities will be supported by members of the Earth Observation research group at Aberystwyth University (in which the position sits). Equally, the role will require working closely with hydrologists at Leeds University (project lead), and malaria experts at the Ministry of Health, Zambia. As such, the RA will be required to communicate their progress with project partners and respond to the needs of the project.

To make an informal enquiry, please contact Prof Andy Hardy at [e-mail].

Appointments are normally made within 4 - 8 weeks of the closing date.

What you’ll do

This job description is subject to review and amendment in the light of the changing needs of the University, to provide appropriate development opportunities and/or the addition of any other reasonable duties.

The specific objectives of this role are to:

• Develop a comprehensive training data set (i.e. annotated satellite imagery) representing target malaria aquatic habitat types (notably, river corridors)
• Deploy the training data set within Deep Learning pipelines developed by the Earth Observation research group (organised as code blocks within a Python notebook).
• Evaluate the output maps both as an iterative process to determine changes in the Deep Learning pipeline, and as a formal validation of final maps.
• Deploy the final model to produce malaria habitat maps
• Assist in writing an academic paper to publish the methods and findings of this work.

To achieve these objectives, the following activities will be carried out:

• Collation of existing datasets on malaria habitat location
• Develop composites of satellite imagery (likely PlanetScope imagery)
• Manually digitise satellite imagery with known malaria habitats within a GIS environment
• Modify Python notebook to read and process the training dataset and satellite image composites within an established Deep Learning pipeline
• Monitor outputs, alongside project partners, to determine modifications of the pipeline to improve the model
• Validate the final model and final output map
• Collate details of the approach and findings to present to the wider project team
• Contribute to a publication reporting the approach and findings

Additionally, you will be required:

• To undertake health and safety duties and responsibilities appropriate to the post.
• To be committed to the University’s Equal Opportunities and Diversity Policy, together with an understanding of how it operates within the responsibilities of the post.
• To be committed to your own development and that of your staff through the effective use of the University’s Effective Contribution Scheme.
• Any other reasonable duties requested commensurate with the grade of this role.
• Undertake other duties as assigned by your line manager, commensurate with the role's grade.
• Engage in university-level projects and initiatives as directed, and undertake any additional duties commensurate with the role, as assigned by the line manager.
• Demonstrate flexibility by supporting colleagues during periods of high demand, including attendance at key university events such as open days and graduation ceremonies which may include weekend work.
• Promote equality of opportunity, and to support and uphold the University's commitment to diversity and inclusion in all aspects of your work.
• To support the university strategy and underlining plans, engage in continuous personal and professional development in line with the demands of the role, including undertaking relevant training and development activities to develop yourself and support the development of others.
• Fulfil health and safety responsibilities appropriate to the role, while actively promoting the personal health, safety, and wellbeing of staff and students as a member of the Aberystwyth community. Additionally, support the University’s commitment to environmental sustainability through responsible practices and engagement.

The above does not represent an exhaustive list of duties associated with this role.

The responsibilities of this vacancy have been matched to the Academic Role Profile Research 1. Details of the role profile can be found at:

https://www.aber.ac.uk/ehr/info-staff/employment/agreement/academic-profiles/#research--(grade-)

Who you are – Qualifications, Experience, Knowledge and Skills required

Essential

1. Experience in Python programming
2. Experience in using cloud-based services like Google Earth Engine and Google Colabs
3. MSc (or equivalent experience) in GIS and remote sensing
4. Working knowledge of GIS platforms, like QGIS.
5. An understanding of different approaches to satellite image classification and validation
6. An ability to understand the bilingual nature of the University and an awareness of the procedures in place to support working bilingually.
7. An ability to understand the bilingual nature of the University and an awareness of the procedures in place to support working bilingually.

Desirable

1. An understanding of the basics of the malaria transmission cycle and the role of surface water
2. Evidence of professional communication skills, including coordination of activities within a group and presentation of work both oral and written
3. Oral (spoken) and Written Welsh Level A1*

*More information on Welsh Language Levels can be found at:

https://www.aber.ac.uk/ehr/policy-and-procedure/welsh-standards/

Benefits

• Flexible working policy
• Hybrid Working
• 36.5 - hour week for full-time roles
• Generous leave entitlements - 27 days annual leave plus bank holidays and university closed days
• Commitment to Professional Development
• Enhanced contribution to our workplace pension schemes
• Staff recognition and reward schemes
• Opportunity to learn the Welsh language for free
• Staff relocation bursary
• Maternity, Paternity, Parental and Adoption Leave
• Staff discount for gym facilities, hospitality, and retail on campus.

Please keep reading

Aberystwyth University generally supports hybrid working, allowing a mix of office-based and remote working for suitable roles to enhance flexibility and productivity. Job descriptions typically detail a primary work location alongside opportunities for flexible, remote, or home-based work, subject to service needs and manager approval.

We welcome applicants from all backgrounds and communities and, those that are currently underrepresented in our workforce. This includes but is not limited to Black, Asian and Minority Ethnic candidates, candidates with disabilities, and female candidates.

We are a Bilingual Institution which complies with the Welsh Language Standards and is committed to Equal Opportunities. You are welcome to apply for any vacancy in Welsh or English and any application submitted will be treated equally.

Employment Visa

Under the UK Government’s points-based system scheme, this role does not meetthe criteria to be sponsored by Aberystwyth University (AU) for a Skilled Worker Route (SWR) application.