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Energy–Transport System Modelling for ASEAN (dual placement)

This project aims to develop an integrated, policy-relevant model of the ASEAN energy–transport system to explore pathways for decarbonising passenger or freight transport while safeguarding reliability and affordability at regional scale.

Scope and approach

  • Geographic focus: ASEAN region as a whole.
  • Tools: LEAP (the Low Emissions Analysis Platform) https://leap.sei.org/default.asp?action=home
  • Outputs should support comparative insights across ASEAN states (e.g., electricity mix, charging demand, fuels, infrastructure needs, emissions).

Collaboration format (two students)

  • KTH Royal Institute of Technology student (Stockholm-based): lead model architecture and scenario design
  • Bangkok-based student (SEI Asia): lead data gathering, quality checks, and contextualisation (policies, technology uptake, costs, activity data)
  • Joint work: harmonised dataset, shared repository, weekly coordination, modelling, and co-authored publication summarizing project findings (peer-reviewed article or brief). SEI and KTH will facilitate local contacts and data sharing.

Key tasks

  • Define system boundaries and scenarios (baseline and 2–3 policy/technology cases).
  • Compile and harmonise national and/or regional data (activity, technology stocks, efficiency, energy prices, policies).
  • Build the model, document assumptions, and run scenarios.
  • Analyse results (energy use, emissions, costs, infrastructure implications; simple sensitivity tests).
  • Produce a concise master thesis report and executive summary.

Expected deliverables

  • Calibrated regional model files and a clean input dataset with sources.
  • Short methods note (model structure, assumptions, uncertainties).
  • Master thesis report in line with university guidelines.
  • Each student will submit a seprate master thesis report to their university.
  • Presentation to KTH and SEI teams. Where appropriate, a co-authored SEI working paper.

Supervision and support

  • Joint supervision from KTH and SEI.
  • Access to model licenses and community resources.
  • Introductions to regional experts for data validation.
  • Hosting at SEI Asia for field work and data collection.

Candidate profile

  • Master thesis level
  • KTH student: energy systems/transport background; very comfortable with modelling (LEAP/OSeMOSYS or similar).
  • Bangkok-based student: strong data skills and policy awareness; ability to source and interpret regional statistics and policy documents, beginner at modelling.

Timing

Start date flexible (late 2025–early 2026); typical duration over one academic semester. The two theses run in parallel with coordinated milestones.

About the internship

This is an internship opportunity that supports your university thesis through knowledge sharing and data collection. SEI staff will provide mentoring, contacts and data, but SEI is not the principal thesis supervisor and is not involved in thesis assessment or grading. Your principal supervisor and examiner are appointed by your home university.

About SEI

SEI Stockholm Environment Institute is an international non-profit research institute that tackles environment and sustainable development challenges. We empower partners to meet these challenges through cutting-edge research, knowledge, tools and capacity building. Scientific quality and integrity are foundations of our work. Partnership is at the heart of our approach, leading to change that lasts.

Our work connects science to policy and practice, aiming to drive tangible impacts. It spans climate change, natural resources, water, air, and health, and addresses questions of governance, innovation, finance, poverty, gender equality and social equity. Through SEI’s HQ and seven centres around the world, we engage with policy, practice and development action for a sustainable, prosperous future for all.

Application

Please send a single PDF with: (i) 1‑page motivation indicating which role you seek (KTH or Bangkok) and preferred tool, (ii) CV and transcript

Contacts

SEI HQ: Maria Xylia (maria.xylia@sei.org)

SEI Asia: Stefan Bössner (stefan.boessner@sei.org )

KTH: Francesco Gardumi (gardumi@kth.se)

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Experimental analysis of waste heat recovery systems for telecommunication base stations
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Development of AI-Based Data-Driven Aging Model for Li-Ion Batteries
Investigations on heat-transfer in a rotating heat-pump
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Calibration of a measurement system for methane pyrolysis detection in rocket nozzles
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