Job Description

To design, build, and maintain hybrid scientific data platforms, focusing on backend systems that support both cloud-based and on-premise infrastructures. The role enables secure, human-centred analysis and sharing of scientific data to advance research in neuroscience and human cognition

Why Join Us:
You will be part of a passionate, interdisciplinary team of scientists and engineers working at the intersection of data science, neuroscience, and human behaviour. Your work will directly support research that deepens our understanding of human cognition and performance.

Duties and Responsibilities:

• Backend Engineering & Data Infrastructure
  • Design, deploy, and maintain cloud-based and on-premise databases (relational and non-relational).
  • Develop and manage ETL pipelines for structured data ingestion and transformation for analytics and machine-learning models.
  • Ensure scalability, security, version control, and documentation of all systems.
  • Build and maintain RESTful APIs or equivalent for interfacing with other components.
  • Implement and monitor security protocols including penetration testing, version compatibility, access control, and malware protection.
  • Configure and maintain access to on-site servers (e.g., Synology NAS, Linux HPC nodes) including network routing, backups, and remote access.
• Cloud and DevOps Engineering
  • Use Firebase (Database, Cloud Functions, Cloud Messaging, Authentication, Analytics) to build real-time, scalable cloud applications.
  • Manage deployment lifecycles, CI/CD pipelines, monitoring, and troubleshooting across cloud environments.
• Data Management for Science
  • Design and maintain systems for versioned data storage, documentation, and sharing of large scientific datasets
  • Support compliance with open science and reproducibility best practices
  • Experience developing tablet-based user interfaces (Unity or web frameworks) is an advantage as well.

Qualifications

• Bachelor’s degree or equivalent in computer science, software engineering, data engineering, or a related technical disciplines.
• Strong proficiency in backend languages (e.g., Python, Node.js, Go) and major cloud services (Firebase, GCP, AWS).
• Experience with SQL and NoSQL database design, deployment, and maintenance.
• Knowledge of DevOps practices, version control (e.g. Git), and automation tools.
• Comfortable with network protocols, firewalls, and Linux system administration.
• Excellent written communication and documentation skills.
• Prior experience supporting scientific, research, or UI/UX projects is highly desirable.