Job Description

Research and Project Development

Research Programmer Intern

Why work with us

At CECCS, you’ll work on real research problems in environment–energy–climate change, alongside a young, dynamic team and experienced researchers. Our work is practical, data-driven, and often requires iterating, debugging, and improving outputs until they are genuinely reliable.

You will also have opportunities to:

  • Learn directly from researchers with strong academic and applied backgrounds

  • Work on problems that require careful computation, reproducible workflows, and high-quality outputs

  • Apply techniques you’ve learned (data science / AI / optimization / geospatial / modeling) to real-world projects, not just classroom exercises

Tools and resources provided for the role

To do the work effectively, we provide access to professional tools and infrastructure as needed, such as:

  • Premium AI subscriptions for research productivity, depending on availability and task needs.

  • A collaborative workspace built around practical research workflows, including documentation, versioning, reproducibility, and review cycles.

  • Access to suitable computational hardware for computationally intensive tasks, including optimization, large-scale runs, or model training when appropriate.

These are provided primarily as work-enabling tools , but they also make a meaningful difference in how much you can learn and build during the role.

Research exposure and publication opportunities

Depending on project needs and your performance, you may have opportunities to contribute to:

  • Internal working papers and research deliverables.

  • Conference submissions and/or journal-oriented outputs where appropriate.

  • Collaboration and academic exchange with external researchers and institutions, including experienced international collaborators.

We keep expectations objective and realistic : publication is not guaranteed, but strong contributors may get meaningful exposure to academic-quality work and writing processes.

Specialty Tracks

Energy Systems, Optimization & Numerical Modelling

Power systems, renewable integration, operations research, scenario modelling, resource planning, and numerical workflows for energy-climate questions.

Remote Sensing, GIS & Environmental Data

Satellite data, geospatial analysis, land use, climate and environmental datasets, map-based evidence, and spatial validation workflows.

Machine Learning, Forecasting & Scientific Computing

Transfer learning, time-series forecasting, applied ML, Python/Julia/R pipelines, reproducible notebooks, and model validation.

JOB DESCRIPTION

1. Support in Data Collection & Analysis

  • Search, filter, and validate data from websites, reports, public datasets, geospatial/satellite sources, and APIs

  • Organize datasets such as electricity demand, weather, wind/solar resources, land use, infrastructure, policy indicators, or economic variables.

  • Use Excel, Google Sheets, GIS tools, Python where applicable, and AI tools to clean, summarize, visualize, and check data.

  • Create summary tables tracking developments or policies in science, technology, climate, environment, and energy fields

2. Support in Research Model Development

  • Learn how research teams turn real-world problems into data, maps, models, and reports.

  • Support Python notebooks or spreadsheets for data cleaning, visualization, model testing, or validation.

  • Help prepare inputs for remote sensing, GIS analysis, time-series forecasting, machine learning, transfer-learning experiments, or energy-system scenario models.

  • Compare model outputs, maps, charts, or forecasts and write short notes on what looks reasonable, what changed, and what needs checking.

3. Reporting & Documentation

  • Help consolidate analytical results into reports (Word, PowerPoint, Google Slides).

  • Create clear and concise presentation slides.

  • Participate in infographic creation and support internal communications.

💡Note: This role is for candidates who want to build reliable research outputs, not just finish tasks.

REQUIREMENTS

1. Candidate Background

  • 4th-year university students or recent graduates from Environment, Economics, Data Science, IT, Engineering, Geography, Remote Sensing, Statistics, or any discipline with strong analytical thinking.

  • Able to read English documents; basic communication is a plus.

  • Familiar with office tools, Google Drive/Docs, Notion, and AI tools.

  • Bonus: Python, GIS, remote sensing, machine learning, transfer learning, time-series forecasting, energy systems, or environmental data.

2. Basic Skills

  • English: Able to read and comprehend documents; basic communication is a plus (IELTS ~6.0+ or equivalent).

  • Proficient in office tools (Word, Excel, PowerPoint), familiar with Google Drive/Docs, Notion.

  • Familiar with AI tools (ChatGPT, Claude AI, etc.) for search, summarization, and outlining tasks.

  • Bonus: Experience with Python, GIS, or other data analysis tools (you’ll be guided – no need to be an expert).

3. Personal Qualities

  • Careful, responsible, organized, and willing to check details.

  • Curious about research, data, and practical climate-energy-environment problems.

  • Able to learn new tools quickly and communicate progress clearly.

  • Comfortable working through ambiguity with guidance from senior researchers.

BENEFITS

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Role Fit

Experience: No in-depth experience required; best for strong students or recent graduates.

This position is especially suitable for candidates who are strong in analytical thinking, willing to learn by doing, and motivated by real projects rather than only classroom-style assignments.

Note: Please clearly express your strengths, goals, and relevant project experience in your CV or cover letter so we can assess fit properly.

  • Full-time stipend from 7,000,000 VND/month; part-time negotiable.

  • Professional working environment with access to international research projects.

  • Opportunities to participate in Ministry- or State-level science and technology projects.

  • Opportunities to develop technical skills in forecasting, GIS/remote sensing, ML or transfer learning, optimization, model validation, visualization, and research communication.

  • Opportunities to build and expand your professional network.

💡 Note: We highly value your learning spirit and willingness to "try – fail – improve."

Please clearly express your strengths and goals in your CV/cover letter so we can best support your internship journey. Good luck!

 FAQs

  • At CECCS, you’ll work on real research problems in environment–energy–climate change, alongside a young, dynamic team and experienced researchers. Our work is practical, data-driven, and often requires iterating, debugging, and improving outputs until they are genuinely reliable.

    You will also have opportunities to:

    • Learn directly from researchers with strong academic and applied backgrounds

    • Work on problems that require careful computation, reproducible workflows, and high-quality outputs

    • Apply techniques you’ve learned (data science / AI / optimization / geospatial / modeling) to real-world projects, not just classroom exercises

    Tools and resources provided for the role

    To do the work effectively, we provide access to professional tools and infrastructure (as needed), such as:

    • High Performance Computing Cluster (HPCC) access for computationally intensive tasks (e.g., optimization, large-scale runs, or model training when appropriate)

    • Premium AI subscriptions for research productivity (e.g., ChatGPT Plus, Gemini Advanced/Pro, NotebookLM Pro, etc., depending on availability and task needs)

    • A collaborative workspace built around practical research workflows (documentation, versioning, reproducibility, review cycles)

    These are provided primarily as work-enabling tools—but they also make a meaningful difference in how much you can learn and build during the internship.

    Research exposure and publication opportunities

    Depending on project needs and your performance, you may have opportunities to contribute to:

    • Internal working papers and research deliverables

    • Conference submissions and/or journal-oriented outputs (where appropriate)

    • Collaboration and academic exchange with external researchers and institutions

      • including experienced international collaborators (e.g., US-based academic partners)

    We will always keep expectations objective and realistic: publication is not guaranteed, but strong contributors may get meaningful exposure to academic-quality work and writing processes.

  • If you are shortlisted, you will receive an email with a link to choose your interview time. Please note that due to limited interview slots, we encourage you to schedule your interview as soon as possible upon receiving the email. Interviews are typically held within 2–3 days after the invitation is sent. If you are not selected, we will notify you via email once the final candidate has been confirmed.

  • Our hiring process includes two stages:

    1. An online test, which you will complete and submit through a provided form.

    2. A single in-person interview at our office if you pass the initial screening.

  • Our company culture values continuous learning, self-discipline, and deep focus. As a research-driven organization, the work here tends to be more individual than team-based, with a strong emphasis on technical depth and logical thinking. Most of our team members are in their 20s and 30s, which makes for a relaxed and friendly work environment despite the intellectually demanding nature of our projects.

  • We’re a compact team composed solely of data analysts and researchers focused on environmental, economics, energy, renewable energy and climate-change studies. New team members will independently tackle diverse project components and, when needed, collaborate in small teams.

  • Headquarters and most staff are based in Hà Nội + remote collaborators across from San Diego, to Galway, to Toronto, to Atlanta, to lowa, to Chapel Hill, across multiple time zones.

  • You can expect to hear from us within 1–2 weeks after submitting your application — possibly sooner, depending on the volume of applicants and internal review timelines.