Grants for new projects 2026
Six new doctoral student grants totalling 43,350,000 kr
- Grant recipient: Ágúst Valfells
- Department: Verkfræðideild/Department of Engineering
- Doctoral Student: NN
- Supervisor: Ágúst Valfells
- Project title: Tölvuhermanir á stakrænum eiginleikum
- hlaðinna agna í lofttóms-díóðum / Computer simulations of discrete charge dynamics in vacuum diodes
Short description of the project:
The proposed project concerns the development and use of high-fidelity molecular dynamics (MD) software for accurate and self-consistent simulations of the effects of discrete electrons on electron emission and propagation in vacuum electronics devices. The work proposed is uniquely capable of capturing important physical mechanisms such as electron-electron scattering and granularity of spacecharge influenced emission from micro-structures, that are inherently important for design and analysis of charged particle sources. It is proposed to use machine learning techniques informed by physical insight, and trained with data from MD simulations, to produce reduced order models for accurate and representative boundary conditions used in commercial and computationally efficient particle-in-cell codes. The MD code will also be improved by adding capabilities for strong-field emission, detailed ionization models, and dynamic change of source term electrons in conductors and dielectric core-shell nanowires. These capabilities will be used to explore how discrete space-charge has an effect on ultrafast emission and cathode breakdown, and rapid modulation of current from core-shell nanowires.
An explicit aim of the project is to not only improve the capabilities of the RUMDEED code and use it for basic scientific research, but also to ensure proper documentation and curation of the code and provide tutorial cases so that the software is freely available and accessible for all.
- Grant recipient: Hlynur Stefánsson
- Department: Verkfræðideild/Department of Engineering
- Doctoral Student: NN
- Supervisors: Hlynur Stefánsson, Guðfinna Th Aðalgeirsdóttir
- Project title: Áhrif örplasts á orkubúskap við yfirborð jökla / The Impact of Microplastics on Glacier Albedo and Melt Dynamics
Short description of the project:
This PhD project investigates how microplastic (MP) pollution affects the reflectivity (albedo) of snow and ice and its potential to accelerate glacier melt. While black carbon and mineral dust have been studied as contributors to reduced albedo, the role of MPs, recently found in glacial regions such as Iceland’s Vatnajökull ice cap, remains poorly understood. The project hypothesizes that MPs embedded in snow and ice lower albedo and increase solar energy absorption, thereby enhancing melt rates.
Through a combination of fieldwork, laboratory experiments with synthetic glacier ice, and glacier energy balance modelling, the research will quantify the effect of MP contamination on melt dynamics under varying conditions. Key research questions address how MPs are incorporated into snow and ice, how their characteristics influence radiative absorption, and how they affect glacier melt models. The project builds on the Icelandic Research Fund project “Microplastics in Glaciers” and benefits from expert supervision and established infrastructure. It is the first study to experimentally and numerically assess MP-induced albedo changes, contributing critical insights into the intersection of plastic pollution and cryospheric change. Findings will inform glaciological forecasting, climate modelling, and environmental policy.
- Grant recipient: Muhammad Taha Sultan
- Department: Verkfræðideild/Department of Engineering
- Doctoral Student: NN
- Supervisor: Muhammad Taha Sultan
- Project title: Smart Windows with Integrated SelfCleaning and Air Quality Monitoring (SWIM)
Short description of the project:
Building infrastructure significantly contributes to global greenhouse gas emissions, with central heating and air-conditioning accounting for approximately 30-40% of these emissions. This necessitates the development of energy-efficient technologies and intelligent building designs to reduce energy consumption while maintaining occupant comfort. Smart windows, which adapt their spectral properties to natural climatic changes or occupant preferences, are a promising solution for improving energy efficiency in buildings. This study proposes the design and fabrication of thermochromic smart windows with integrated self-cleaning and air quality management features. Vanadium dioxide (VO₂) will be used for its near-room-temperature phase transition, enabling passive modulation of optical properties without external energy. Titanium dioxide (TiO₂) will provide self-cleaning properties, while zinc oxide (ZnO) will contribute to air purification by reducing indoor pollutants such as volatile organic compounds (VOCs). The effectiveness of these smart windows will be assessed through a comprehensive comparison with commercially available alternatives, focusing on energy efficiency, cost, solar transmittance, power consumption, and reliability. The study seeks to advance energy-efficient building solutions and strengthen expertise in functional materials and solid-state physics in Iceland’s research community.
- Grant recipient: Kaustab Chandra Sahu
- Department: Verkfræðideild/Department of Engineering
- Doctoral Student: Kaustab Chandra Sahu
- Supervisor: Slawomir Koziel
- Project title: Deep Neural Surrogates for Accurate and Design-Ready Modeling of High-Frequency Systems
Short description of the project:
The design of high-frequency systems, such as antennas and microwave circuits, has become increasingly complex due to modern performance requirements, including multiband support, reconfigurability, and compact topologies. These challenges necessitate full-wave electromagnetic (EM) simulations, which are computationally intensive and inefficient for iterative design and optimization.
This project proposes developing deep neural surrogate models for both forward EM response prediction and inverse geometric parameter estimation, focusing on high-frequency systems with complex geometries. Recurrent Neural Networks (RNNs), attention mechanisms, and deep residual architectures will be employed, treating frequency as a sequential input for improved generalization.
Preliminary results demonstrate strong potential for performance improvements over existing surrogate models. The project will contribute to electromagnetic computation by significantly reducing simulation costs, enabling data-efficient inverse design, and advancing the application of AI in EM design workflows. Experimental validation and publication of developed models will support the project's scientific and technological impact, particularly for next-generation applications in IoT, 5G, and satellite communication.
- Grant recipient: Anna-Lena Bracksieker
- Department: Sálfræðideild / Department of Psychology
- Doctoral Student: Anna-Lena Bracksieker
- Supervisor: Rannveig Sigríður Sigurvinsdóttir
- Project title: I Will Survive (and Grow): Understanding Mediating and Moderating Factors of Posttraumatic Growth and Well-being in Iceland
Short description of the project:
Posttraumatic growth (PTG) describes positive psychological change following trauma, such as improved relationships, personal strength, or life appreciation. Although women consistently report higher PTG than men, the mechanisms behind this gender difference remain unclear. Factors like social support and socioeconomic status (SES) have been linked to PTG, yet their interaction with gender is underexplored.
Additionally, romantic relationships—key sources of support and identity—have received little attention in PTG research.
This PhD project uses longitudinal data from the nationally representative Icelandic Mental Health Study to investigate how gender, SES, social support, and relationship dynamics relate to PTG.
Study 1 examines whether SES predicts PTG via perceived social support, moderated by gender. Study 2 explores whether relationship satisfaction, emotional intimacy, and sexual well-being relate to PTG, also moderated by gender.
Study 3 applies a person-centered approach to identify distinct PTG trajectories over time and examines how gender, prior trauma exposure, and COVID-19-related adversity predict trajectory membership and mental health outcomes.
Together, these studies aim to clarify how social and relational factors shape PTG, provide insight into gendered responses to trauma, and lay the groundwork for future studies on gender-sensitive approaches to trauma recovery.
- Grant recipient: Ender Demir
- Department: Department of Business and Economics
- Doctoral Student: NN
- Supervisor: Ender Demir
Project title: Digital Currency Literacy Index - A Framework for Measuring and Advancing Digital Currency Understanding Across Countries
Short description of the project:
The Digital Currency Literacy Index (DCLI) project aims to develop a validated, multidimensional index to measure digital currency literacy across diverse countries. As digital assets and blockchain technologies increasingly shape global finance, individuals and policymakers alike require new tools to assess knowledge and preparedness. Despite growing adoption, there is little consensus on how to define or measure digital currency literacy, particularly across financial, technical, behavioral, and policy dimensions. This project addresses the gap by constructing an index of those dimensions, developed through an interdisciplinary workshop. The project includes large-scale data collection in Iceland and comparative surveys in Norway, Poland, Turkey, the UK, and Singapore. It will examine demographic disparities, the relationship between digital currency literacy and financial decision making.
Outputs include a cross-country comparable literacy index, academic publications, policy briefs, and education tools. By aligning local insight with global needs, the DCLI will help guide safe, inclusive, and informed adoption of digital financial technologies.