Junior Research Assistant in Research and Reproducibility

Utrecht University; Netherlands; On-site; EUR 36,000 - 46,000; Part time

Benefits offered by this job

Pension scheme

Flexible leave arrangements

Personal and professional growth

8% holiday pay

8.3% year-end bonus

Job summary

Utrecht University seeks a Senior Research Assistant to own the reproducible data pipeline and reporting infrastructure within the PPBS project. You will maintain the public website, shared research infrastructure, and implement decisions into reliable follow-through.

You will work under the direction of PPBS leaders and embedded researchers, independently managing technical operations while scientific choices remain with supervisors. Strong R, Git, and project management are essential.

Qualifications

• Master's degree or equivalent professional experience in social science, data science, or related field.
• At least three years of relevant experience after the Master’s degree in research data, reproducible reporting, or related work.
• Ability to understand, run, debug, and improve a substantial inherited workflow in R.
• Strong knowledge of R Markdown and/or Quarto, tidy data workflows, data validation, and automated report generation.
• Experience cleaning, recoding, labeling, documenting, and quality-checking complex survey or social-science data.
• Proficiency with Git and GitHub, including branches, commits, pull requests, conflicts, and collaboration.
• Ability to understand and maintain a research website built from a version-controlled repository.
• Strong project-management habits: agenda, minute-taking, task tracking, prioritisation, follow-through.
• Fluent written and spoken English for precise records and implementation steps.
• Good judgement on when to solve operational problems and when to elevate scientific decisions.

Responsibilities

• Own the technical operation of the reproducible data pipeline and reports.
• Maintain PPBS website repository and publication workflow in GitHub.
• Organise research files across Dropbox, Google Drive, and GitHub with provenance and versioning.
• Prepare meeting agendas and minutes; track decisions and dependencies; follow up with contributors.
• Identify risks early and propose proportionate solutions; escalate as needed.
• Ensure pipeline is organized, documented, reproducible, and moving forward.

Skills

R programming

Data wrangling

Reproducible reporting

Git versioning

English communication

Project management

Education

Master’s degree in social science or related field

Tools

Git

GitHub

R

R Markdown

Quarto

Job description

Organisation/Company Utrecht University Research Field Political sciences » Governance Psychological sciences » Psychology Researcher Profile Recognised Researcher (R2) Application Deadline 4 Oct 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 24.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Do you combine strong R skills with the ability to bring structure to complex collaborative research? The Psychology of Political Behavior Studies (PPBS) is looking for a senior research assistant to independently operate our reproducible data and reporting pipeline, maintain our website and shared research infrastructure, and turn meetings and decisions into reliable follow-through. You will work within an international political psychology programme under the direction of Dr Flavio Azevedo and Jasmin Haggemann.

Your job

The Psychology of Political Behavior Studies (PPBS; ppbs.science ) is a longitudinal research programme examining political attitudes, identities, behaviour, and psychological constructs across multiple survey waves, samples, panel providers, and countries. PPBS maintains linked codebooks, data-processing workflows, reproducible reports, a public website, and shared research and project-management infrastructure.

As Senior Research Assistant in Research Operations and Reproducibility, you will ensure that this infrastructure is organised, documented, reproducible, and moving forward. You will work under the direction of Dr Flavio Azevedo and Jasmin Haggemann. You will independently own the technical operation of the pipeline, while scientific, measurement, ethical, and strategic decisions remain with the supervisors and relevant PPBS researchers.

Your core tasks include:

• running, maintaining, debugging, documenting, and incrementally improving PPBS workflows in R and R Markdown or Quarto;
• managing the progression from raw survey exports to cleaned, labelled, processed, validated, and versioned analysis-ready datasets without compromising source-data integrity;
• maintaining reproducible construct reports with descriptive statistics, scale reliability, tables, figures, and transparent analytical documentation;
• implementing and checking variable recoding, value labels, missing-data rules, reverse scoring, derived variables, composite scores, and cross-wave harmonisation;
• generating and maintaining empirical codebooks, data dictionaries, metadata outputs, construct specifications, and validation checks;
• maintaining the PPBS website repository and publication workflow in GitHub, including routine content and report updates and diagnosis of build or deployment problems;
• organising research files and documentation across Dropbox, Google Drive, and GitHub, with clear provenance, naming, versioning, access, and release status; preparing meeting agendas and minutes, recording decisions and dependencies, maintaining action trackers, coordinating hand-offs, and following up with contributors; and
• identifying operational and reproducibility risks early, proposing proportionate solutions, and escalating decisions that require scientific or managerial authority.

Because the appointment is short and part‑time, the immediate priority is reliable pipeline and report ownership, followed by operational coordination and routine website maintenance. Major software redevelopment or independent statistical research is outside the role unless separately agreed and resourced.

We believe in a balance between individual and collective achievements. That is why we assess both individual and team performance. We encourage staff members to share scientific knowledge, document their work transparently, and contribute to a constructive and inclusive working environment. We are looking for a systematic and dependable colleague who can work independently on technical operations while collaborating closely on scientific decisions. You meet the following requirements:

• you have completed a Master’s degree in social science, data science, research methods, statistics, or a related field, or demonstrate an equivalent level of professional expertise;
• you have at least three years of relevant experience after your Master’s degree, or equivalent professional experience, in research data, reproducible reporting, research software, or closely related work;
• you can independently understand, run, debug, and improve a substantial inherited workflow in R;
• you have strong working knowledge of R Markdown and/or Quarto, tidy data workflows, data validation, and automated report generation; you have experience cleaning, recoding, labelling, documenting, and quality‑checking complex survey or social‑science data;
• you are competent with Git and GitHub, including branches, commits, pull requests, conflict resolution, issues, and collaborative review;
• you can understand and maintain a research website built from a version‑controlled repository;
• you have strong project‑management habits, including agenda preparation, minute‑taking, task tracking, prioritisation, and dependable follow‑through;
• your written and spoken English enables you to turn complex or ambiguous discussions into precise records, specifications, and implementation steps; and
• you exercise sound judgement about when to solve an operational problem independently and when to elevate a scientific, measurement, ethical, or strategic decision.

The following experience is an advantage:

• political psychology, psychometrics, scale construction, reliability analysis, survey methodology, or longitudinal data harmonisation;
• reproducible environment management, automated testing, continuous integration, dependency management, or workflow tools such as targets;
• metadata standards, FAIR principles, data repositories, licensing, disclosure control, or research‑data governance;
• HTML/CSS, static‑site systems, accessible web content, or web deployment workflows;
• responsible use of AI‑assisted coding tools such as Codex or Claude, including verification of generated code and appropriate handling of sensitive information; and
• coordination of distributed, international, interdisciplinary, or volunteer‑based research collaborations.

Additional Information

• a job for for approximately 2.5 months; the exact duration will be determined after the appropriate salary classification;
• a working week of 20 - 24 hours and a gross monthly salary between €3.202 and €4.159 (salary scale 7 under the Collective Labour Agreement for Dutch Universities (CAO NU). The salary is based on a 38‑hour working week;
• 8% holiday pay and 8.3% year‑end bonus;
• a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.

In addition to the terms of employment set out in our collective labour agreement, we offer attractive additional benefits, including opportunities for personal and professional growth , flexible leave arrangements, and extra vacation days. Through the UU Terms of Employment Options Model, you can tailor your employment package to your needs. In this way, we encourage you to grow in what you do, both in your work and in your development. Read more about our terms of employment.

Selection process

At Utrecht University, we strive to be a place where everyone feels at home. We value colleagues with different backgrounds, perspectives and identities, including differences in culture, religion or ethnicity, gender, sexual orientation, neurodiversity, disability and age. We are committed to creating a safe and inclusive environment where everyone can thrive and contribute. Read more about our commitment to diversity and inclusion. If you have any questions about accessibility, for example regarding your workplace Sjoerd Groenmangebouw , the application process or your work, please contact us via our HR contact page .

Knowledge security screening can be part of the selection procedures of academic staff. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology.

The selection process will include a short practical exercise using a small, non‑sensitive PPBS‑style dataset and repository. The exercise will assess your ability to understand inherited R code, identify reproducibility risks, implement and validate a limited change, render a report, use Git appropriately, and explain your decisions clearly.

For more information, please contact Dr Flavio Azevedo at [e-mail]

Candidates for this vacancy will be recruited by Utrecht University.