Research Fellow/Research Assistant in GeoAI (Part Time)

TN United Kingdom; London; On-site; GBP 43,000 - 45,000; Part time

Job summary

An established industry player is seeking a Research Fellow/Assistant in GeoAI to contribute to an innovative project focused on synthetic human mobility data generation. This part-time role offers an exciting opportunity to work with leading academics and industry partners, implementing cutting-edge deep learning techniques and developing metrics to assess data reliability. The position not only involves research but also supervision of master students and public engagement through presentations. With a competitive salary and generous benefits, this role is perfect for a motivated individual eager to make a significant impact in the field of spatial data science.

Benefits

41 Tage Urlaub

CARE Pensionsplan

Fahrrad- und Saisonkartenkredite

Unterstützung bei Umzug und Einwanderung

Vor-Ort-Kita und Fitnessstudio

Erweiterte Elternzeitvergütung

Mitarbeiterunterstützungsprogramm

Rabattierte Krankenversicherung

Qualifications

• Proficiency in Python for spatial data analysis and modeling.
• Knowledge of urban mobility analysis and applications.

Responsibilities

• Review literature on synthetic data generation and applications.
• Implement state-of-the-art deep learning methods.
• Collaborate on realTRIPS projects and publish findings.

Skills

Python für räumliche Datenanalyse

Stadtmobilitätsanalyse

Mobile Datenverarbeitung

ML/DL Methoden

Forschungswerkzeuge entwickeln

Literaturrecherche

Kommunikationsfähigkeiten

Forschungsveröffentlichungen

Education

PhD in einem relevanten Bereich

Job description

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Research Fellow/Research Assistant in GeoAI (Part Time), London

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Client:

Location:

London, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Reference:

cd2cbfcf6c84

Job Views:

4

Posted:

28.04.2025

Expiry Date:

12.06.2025

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Job Description:

About the role

This research role is on the PHOTO – ERC-funded Proof of Concept project, related to the ERC starting grant project – realTRIPS. PHOTO aims to develop a prototype human mobility trajectory data generator, producing synthetic human trajectory data from original mobile in-app data. The synthetic data should enhance the original data while preserving essential human mobility patterns. The role involves working closely with academics at the Centre of Advanced Spatial Analysis (Dr Chen Zhong) and other team members on the realTRIPS project at UCL, as well as with industrial partners on urban mobility applications. Responsibilities include:

1. Review literature on synthetic data generation and applications in human mobility.
2. Implement and compare state-of-the-art deep learning methods.
3. Design new methods for generating synthetic urban-scale trajectory data based on real-world mobile and survey data.
4. Develop metrics to assess the reliability of synthetic data in various scenarios.
5. Participate in research meetings and project discussions.
6. Supervise master student projects relevant to the research.
7. Collaborate on realTRIPS projects and with CASA colleagues.
8. Publish research findings in conferences and journals.
9. Share outputs through presentations and public engagement.
10. Follow research ethics, data security, and data management guidelines.

The position is part-time, starting from 1 May, funded until 30 September. Salary ranges from £43,000 to £45,000 pro rata per annum, including London Allowance. If the candidate does not yet have a PhD, the initial appointment will be at Grade 6B (£38,000–£41,000), with backdated Grade 7 payment upon PhD completion. The role adheres to UCL terms and conditions. Flexible and part-time applications are welcome. For inquiries, contact Chen Zhong. To apply, click ‘Apply Now’.

About you

The candidate should have a PhD in a relevant field (e.g., spatial data science, computer science, GIS). Essential skills include:

• Proficiency in Python for spatial data analysis and modeling.
• Knowledge of urban mobility analysis, modeling, and applications.
• Experience with mobile human mobility data and data preprocessing.
• Strong understanding of ML/DL methods, including Transformers, RNN, LSTM, and Generative AI.
• Experience developing reusable code and research tools.
• Ability to review and synthesize research literature systematically.
• Excellent communication skills for diverse audiences.
• Proven research publication record.
• Flexible, motivated, and organized with the ability to manage workload and meet deadlines.

For full criteria, refer to the detailed job description and person specification.

What we offer

Benefits include:

• 41 days holiday (27 days annual leave, 8 bank holidays, 6 closure days).
• Additional 5 days’ leave purchase scheme.
• CARE pension scheme.
• Cycle to work and season ticket loans.
• Relocation and immigration support.
• On-site nursery and gym.
• Enhanced maternity, paternity, and adoption pay.
• Employee assistance program and discounted health insurance.