Job Description

Research and Project Development

Research Programmer Trainee (Energy Modelling)

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.

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

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.

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.

JOB DESCRIPTION

1. Data Collection and Analysis

  • Collect, clean, validate, and document datasets from reports, APIs, satellite/geospatial sources, academic papers, and public databases.

  • Work with tabular data, geospatial layers, satellite-derived data, time-series data, and model outputs.

  • Build clear data-processing workflows so datasets can be reused, checked, and connected to research models.

2. Research Model Development

  • Develop or adapt workflows for time-series forecasting, remote-sensing analysis, transfer learning, optimization, and energy/environmental scenario modelling.

  • Translate real-world research questions into datasets, model inputs, assumptions, features, constraints, and validation checks.

  • Build reproducible Python/R/Julia workflows for data processing, model execution, comparison, and visualization.

  • Adapt methods from scientific papers into practical research workflows suitable for CECCS projects.

3. Reporting and Documentation

  • Compile analytical outputs into scientific reports, policy briefs, or presentation decks.

  • Prepare visual assets that clearly communicate findings.

  • Draft research plans for future projects and innovation initiatives.

REQUIREMENTS

1. Candidate Background

  • Bachelor's degree in Environmental Engineering, Computer Science, Data Science, Data Analysis, Climate, Energy, Remote Sensing, Geography, Statistics, or Sustainable Development.

  • Experience: Minimum 6 months of relevant experience.

  • Solid foundation in Python, R, or Julia for data processing.

  • Experience with computational modelling, optimization, forecasting, or applied ML is preferred.

  • GIS, remote-sensing, time-series forecasting, and/or AI/ML based analysis experience is a plus.

2. Skills

  • Language: Proficient in English (IELTS 7.0+ or equivalent).

  • Experience with computational modeling/ optimization modeling/ operations research is preferred.

  • Proficient (or quick to adapt) with AI tools (e.g., ChatGPT, Gemini, Claude) to enhance research productivity.

  • Proficient in documentation software (Word, Excel, PowerPoint), note-taking and cloud storage tools (e.g., Notion, Google Drive).

  • Strong analytical and logical thinking, with a passion for research.

3. Other Requirements

  • 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.

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

BENEFITS

  • 11,000,000-15,000,000 VND/month + performance-based bonus.

  • 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.

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.

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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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.