Masters-students
Available master's projects

Available master's projects

Research areas

Below is a list of the predefined master's thesis projects available at Simula; the list can be sorted according to the research area of interest. 

Read What can we do with a quantum computer with only two or three q-bits?

What can we do with a quantum computer with only two or three q-bits?

Machine Learning

This is in fact a set of possible projects in the fields of AI and quantum computation. We will use the first quantum computers of Norway recently bought by the Department of Computer Science and the OsloMet AI Lab.

Read Visualizing Benefits: A Systematic Approach to Benefits Management via a Digital Platform

Visualizing Benefits: A Systematic Approach to Benefits Management via a Digital Platform

Software Engineering

We are embarking on an exciting project to build a digital platform that tackles one of the most challenging areas for project managers and organizations - Benefits Management. Despite its increasing importance in recent years, many organizations find themselves navigating the complex world of benefits management with no clear direction. This is where you come in. By joining our project, you will be at the forefront of creating a solution that demystifies benefits management. You will help provide clear and streamlined processes for planning, monitoring, and reporting, ultimately leading organizations to success in their benefits management endeavors.

Read Use of a Bayesian Approach for Generating Statistically Representative Sky Signals

Use of a Bayesian Approach for Generating Statistically Representative Sky Signals

Machine Learning, Software Engineering

Apply advanced Bayesian techniques to synthesize statistically representative sky signals. This project focuses on implementing Gibbs sampling for astrophysical data, offering a rigorous approach to overcoming optimization challenges in modern cosmological analysis.

Read Unlocking the Potential of Digital Twins for Software Systems

Unlocking the Potential of Digital Twins for Software Systems

Software Engineering

Crafting digital twins for diverse software systems.

Read Unlock the Future of Medical AI with the Kvasir-VQA Dataset

Unlock the Future of Medical AI with the Kvasir-VQA Dataset

Machine Learning

We aim to benchmark the Kvasir-VQA dataset across various cutting-edge tasks. As a student, you have the flexibility to choose one or multiple tasks that align with your interests and focus your research efforts accordingly.

Read Uncovering extreme climate events with machine learning

Uncovering extreme climate events with machine learning

Machine Learning

One of the most worrisome consequences of climate change for modern societies is the occurrence of extreme events, in particular heatwaves, wildfires and droughts. Extreme events impact not only our environment, but also our economy and health, so our society in general.

Read Uncertainty quantification of missing data

Uncertainty quantification of missing data

Machine Learning

Dive into an experimental study to discover the best methods for quantifying uncertainty when filling in missing values for time series data and how this affects the uncertainty quantification in downstream classification tasks. Potential applications are health care, sport analysis, or lifelogging (the application of your choice).

Read Towards Reliable Solutions from Artificial Intelligence: From Learning to Decision-Making

Towards Reliable Solutions from Artificial Intelligence: From Learning to Decision-Making

Scientific Computing, Machine Learning

How can we use mathematical optimization, uncertainty quantification, and asymptotic statistics to develop a computational framework that takes us from data and training statistical models to actually making robust, risk-averse decisions based on the predictions of these models?

Read Topic Classification of Scientific Papers

Topic Classification of Scientific Papers

Machine Learning

Millions of scientific papers are published very year. Can we use AI to understand their contents?

Read Sport news classification

Sport news classification

Machine Learning

Automatic classification of sport news into different categories using state of the art Natural Language Processing (NLP). The project is building upon an existing dataset of Norwegian soccer news.

Read Sperm-net for ML research

Sperm-net for ML research

Machine Learning

Contribute to the future of AI-driven sperm analysis by curating, organizing, and testing open-access datasets.

Read Securing the AI pipeline: Privacy and security metrics for trustworthy and transparent AI

Securing the AI pipeline: Privacy and security metrics for trustworthy and transparent AI

Machine Learning

Nowadays transparency is an important aspect of the Trustworthiness AI algorithms should have. However, making AI more transparent raises issues concerning privacy and security. How to best balance the transparency an AI algorithm should have for users with an also needed security and privacy of the data it accesses/uses?

Read Real-world optimization and machine learning on quantum computers

Real-world optimization and machine learning on quantum computers

Software Engineering, Machine Learning

Up for quantum-powered solutions to real-world optimization or machine learning?

Read Quantum Software engineering and its applications

Quantum Software engineering and its applications

Software Engineering

Quantum computing is at the edge of a technological revolution, offering you the chance to be part of the innovation that will solve problems once thought impossible. Jump in now and help shape the future of this groundbreaking field!

Read Quantifying individual differences in eye-gaze dynamics

Quantifying individual differences in eye-gaze dynamics

Scientific Computing, Machine Learning

We know some people, such as those with ADHD and autism, tend to gaze at images differently. But at the individual level, could everyone have their “own” way of looking? Can we use this to improve diagnoses and better understand visual search?

Read Programing AMD GPUs for High performance Computing

Programing AMD GPUs for High performance Computing

Scientific Computing, Machine Learning

AMD GPUs are very powerful, but how can we use their full potential?

Read Privacy risk assessment in large-scale measurement datasets

Privacy risk assessment in large-scale measurement datasets

Communication Systems

Evaluate end-user and business privacy in public Internet measurement datasets.

Read Prediction of dry eye disease using metabolomics data

Prediction of dry eye disease using metabolomics data

Machine Learning

Development of methods to improve metabolomics data handling for predicting dry eye disease.

Read Predicting Next Purchase Day and Order Volume for Customers in a Supply Chain

Predicting Next Purchase Day and Order Volume for Customers in a Supply Chain

Machine Learning

TINE SA serves over 20,000 business customers who place orders directly with the company. Each customer exhibits unique purchasing behaviors influenced by various factors, including seasonality and product shelf-life constraints. These behaviors are further shaped by individual seasonality patterns (such as stable or variable seasonal dates, geographically specific holidays, and annual events) and distinct warehouse management strategies (such as stockpiling or maintaining a consistent order policy).

Read Performance monitoring and diagnosis in mobile communication networks

Performance monitoring and diagnosis in mobile communication networks

Communication Systems, Machine Learning

Build an automated system based on machine learning to diagnose fault conditions in mobile communication networks.

Read PCI Express support for BeeGFS

PCI Express support for BeeGFS

Communication Systems, Software Engineering, Scientific Computing

In this master, you will add RDMA functionality to the global shared filesystem BeeGFS™️ (ThinkParQ) when running over PCIe NTB interconnects from Dolphin Interconnect Solution.

Read Parallel implementation of graph neural networks

Parallel implementation of graph neural networks

Machine Learning

Graph Neural Networks are a powerful machine learning technique for unstructured data. How can we make them scale to supercomputers?

Read Optimizing Network Efficiency in Modern Supercomputers

Optimizing Network Efficiency in Modern Supercomputers

Scientific Computing

How can we distribute workloads among compute nodes to make best use of the high speed networks in supercomputers?

Read Next Generation Sport Systems - AI-Based Video Analysis, Processing, and Delivery

Next Generation Sport Systems - AI-Based Video Analysis, Processing, and Delivery

Machine Learning

Interested in sport technology for videos used by elite leagues and live broadcasters? We have for long researched sports technology, both for distributing the video of live broadcasts and managing the archives in Norway and Sweden. We develop systems that are actively used and tested on real users, where the users can see highlights and summaries, get recommendations, collect favorite events, make personalized playlists, etc.

Read Neuro-Symbolic Models for Scene Understanding in Automated Driving

Neuro-Symbolic Models for Scene Understanding in Automated Driving

Software Engineering, Machine Learning

Develop a neuro-symbolic pipeline that combines scene graphs and machine learning to identify relevant objects for automated driving manoeuvres.

Read Multimodal-LLMs for Explanations in Automated Driving

Multimodal-LLMs for Explanations in Automated Driving

Software Engineering, Machine Learning

Evaluate LLMs for enhancing trustworthiness in automated driving through identification of relevant objects and anticipation of their future behaviour and explanation of the actions taken by the car.

Read Monitoring the submarine cable network

Monitoring the submarine cable network

Communication Systems

Build an automated system for monitoring the deployment of submarine cables through large-scale passive and active measurements.

Read Monitoring the hygiene of non-routed space

Monitoring the hygiene of non-routed space

Communication Systems

Develop techniques to enable predictive capabilities in the detection and prevention of misuse of unallocated or allocated IP address space by malicious actors.

Read Monitoring 2d environments with eye-tracking based agents

Monitoring 2d environments with eye-tracking based agents

Scientific Computing, Machine Learning

What kind of environments are our visual search strategies adapted to? Can they be transplanted to autonomous vehicles?

Read Modelling the Heart's Hidden Hero: The Right Ventricle

Modelling the Heart's Hidden Hero: The Right Ventricle

Scientific Computing, Machine Learning

Continuing the quest to unlock the mysteries of right ventricular function through machine learning and computational modeling

Read Modelling the evolution of the New York Stock Exchange

Modelling the evolution of the New York Stock Exchange

Machine Learning

This project handles with the 10-min NY Stock Exchange data between 2011 and 2014 and aims at processing the data and publish it for research purposes.

Read Modelling and simulating the brain's waterscape

Modelling and simulating the brain's waterscape

Scientific Computing

Read Modeling the mechanics of the heart

Modeling the mechanics of the heart

Scientific Computing

The heart is the organ responsible for pumping blood around in your body. The heart consist of a tissue known as myocardium which is known to be a anisotropic, nonlinear, visco-elastic and nearly incompressible material. In order to create realistic models of the mechanics of the heart we would therefore need to incorporate these effects as well as appropriate boundary conditions.

Read Missing Data Imputation in Biology

Missing Data Imputation in Biology

Scientific Computing, Machine Learning

This project aims to evaluate various imputation methods specifically for missing data in biological contexts. The student can also choose to examine the scalability of known methods or to develop new techniques that are scaleable.

Read Malware in Deep Neural Networks

Malware in Deep Neural Networks

Machine Learning

Deep learning systems are becoming increasingly popular, but their security aspects are often overlooked by developers. You will learn how deep neural networks can be used as an attack vector, and either explore how these attacks can be mitigated, or perhaps develop even more effective attacks.

Read LLM-Driven Testing: Assessing Large Language Models in Cancer Registry Applications

LLM-Driven Testing: Assessing Large Language Models in Cancer Registry Applications

Software Engineering, Machine Learning

This research project seeks to transform cancer registry testing by harnessing the power of Large Language Models (LLMs) like ChatGPT, offering automated, generative testing methods to detect anomalies, create test cases, and enhance data quality.

Read Large Language Models Adaptation for Cyber-Physical System Testing

Large Language Models Adaptation for Cyber-Physical System Testing

Software Engineering

Dive into the challenge of testing Cyber-Physical Systems (CPSs) by optimizing and leveraging the potential of Large Language Models (LLMs).

Read Knowledge-guided machine learning for interpretable pattern discovery

Knowledge-guided machine learning for interpretable pattern discovery

Machine Learning

The goal of the project is to develop unsupervised machine learning methods that will guide real data analysis with mechanistic models and reveal interpretable patterns to extract insights from complex data.

Read IPFS for large-scale and long-term DNS data storage and access

IPFS for large-scale and long-term DNS data storage and access

Communication Systems

Evaluate the use of IPFS for massive and large-scale DNS data storage and access.

Read Imputing Missing Data from Methylation Data for Cell Deconvolution Methods

Imputing Missing Data from Methylation Data for Cell Deconvolution Methods

Machine Learning

DNA methylation is a major epigenetic modification of the human genome that affects fundamental biological functions, such as gene expression and cell development. In a simple language, this modification can be likened to a set of traffic lights.

Read Impact of contrastive learning methods for training foundation models in ECG analysis

Impact of contrastive learning methods for training foundation models in ECG analysis

Machine Learning

Dive into an experimental study to discover the best methods for applying contrastive learning to ECG data, including algorithm selection, data pairing techniques, and optimal data formats for deep learning.

Read Image resolution vs sperm analysis using AI

Image resolution vs sperm analysis using AI

Machine Learning

Uncover the impact of image resolution on sperm analysis using machine learning! Dive into an experimental study that explores how video quality influences the accuracy of AI in predicting sperm motility and morphology.

Read Generative machine learning for precision medicine

Generative machine learning for precision medicine

Machine Learning

The accuracy of machine learning models used in clinical decision making has a direct impact on a patient's chances of recovery. Missing data pose a challenge and generative models can assist overcome it.

Read Extracting insights from multiple metabolomics data sets through data fusion

Extracting insights from multiple metabolomics data sets through data fusion

Machine Learning

The project focuses on joint analysis of NMR (Nuclear Magnetic Resonance) spectroscopy measurements of plasma and urine samples as well as faecal metabolome data using interpretable multimodal data mining.

Read Exploring Multidomain Applications of Large Language Models in Software Engineering

Exploring Multidomain Applications of Large Language Models in Software Engineering

Software Engineering, Machine Learning

This project meets the demand for enhanced approaches by harnessing LLMs to elevate software engineering practices in specific research domains.

Read Exploring Missing Data Handling and Batch Effects in DNA Methylation Analysis

Exploring Missing Data Handling and Batch Effects in DNA Methylation Analysis

Machine Learning

DNA methylation is a fundamental epigenetic modification within the human genome, influencing various biological processes, including gene expression and cellular development. In the context of methylation data analysis, values typically range from 0 to 100 (or 0 to 1), depending on the chosen scale.

Read Explainable Reinforcement Learning

Explainable Reinforcement Learning

Machine Learning

In recent years, artificial intelligence has made significant strides in various fields, reshaping the landscape of technology and innovation. One of the key factors driving this progress is the emergence of reinforcement learning (RL) which enables autonomous agents to make decisions and adapt to their surroundings. RL has been very successful in games and other applications. In general, an RL agent aims to learn a near-optimal policy to achieve a fixed objective by taking action and receiving feedback through rewards and observations from the environment. A neural network (NN) commonly represents the policy that, given the observation of the environment state as input, yields values that indicate which action to choose.

Read Explainability of time series missing data techniques

Explainability of time series missing data techniques

Machine Learning

Dive into an experimental study to discover how filling missing values for time series data affects the explainability of a downstream classification task. Potential applications are health care, sport analysis or lifelogging (the application of your choice).

Read Evolving neural networks for optimal foraging

Evolving neural networks for optimal foraging

Scientific Computing, Machine Learning

If a neural network produces an output that switches at random, can evolution be used to shape this noise? Can this help explain the random movement patterns of animals foraging for food?

Read Enhancing Patch Validation in Automated Program Repair through Large Language Models

Enhancing Patch Validation in Automated Program Repair through Large Language Models

Software Engineering, Machine Learning

Investigate and develop methods to confirm the correctness of patches generated by APR systems, leveraging the capabilities of large language models (LLMs).

Read Effects of 5G Rollout on End-User Experience

Effects of 5G Rollout on End-User Experience

Communication Systems

Quantifying the real-life effect of 5G deployment based on Simula's own measurements.

Read Development and Testing of Self-Driving Cars

Development and Testing of Self-Driving Cars

Software Engineering, Machine Learning

Implementing software tools for designing, developing, and testing of self-driving cars.

Read Detecting DDoS Attacks in Programmable Data Planes

Detecting DDoS Attacks in Programmable Data Planes

Communication Systems, Machine Learning

Building a machine learning model using data plane programming language such as P4 that detect network security attacks at line rate with high accuracy

Read Data Traffic Reduction in Active 5G Measurements

Data Traffic Reduction in Active 5G Measurements

Communication Systems

Can we accurately measure the 5G network performance using less data than the standard tools?

Read CPU free Programming: When the GPU takes the Lead

CPU free Programming: When the GPU takes the Lead

Scientific Computing, Machine Learning

New tools can remove inefficiencies in GPU computing, but can we turn that into real performance gains?

Read Combining metrics of energy efficiency and complexity of AI algorithms

Combining metrics of energy efficiency and complexity of AI algorithms

Machine Learning

Nowadays the high performance of AI algorithms developed together with an ever increasing complexity and huge energy cost. This makes nowadays AI less and less sustainable and future AI research should account for these trade-offs.

Read Co-production and co-destruction patterns in systems design, development and use

Co-production and co-destruction patterns in systems design, development and use

Software Engineering

An IT system is meant for creating benefit for both service providers and service consumers. Often, disbenefit is created instead. You will study the phenomena of co-production of benefit and co-destruction into disbenefit in public service IT systems.

Read Classification confidence visualization of artificial neural networks with adversarial robustness

Classification confidence visualization of artificial neural networks with adversarial robustness

Machine Learning

Adversarial attacks can easily fool artificial neural networks. This project aims to understand these attacks and their defenses by visualizing their classification confidence.

Read Building and evaluating a web-based tool for software benefits estimation and management

Building and evaluating a web-based tool for software benefits estimation and management

Software Engineering

To help IT professionals optimize the value for stakeholders, you will develop a set of easy-to-use tool for estimating and monitoring how much potential benefit a system under development will produce. You will design the tool based on recent theoretical results, and you will test and evaluate the tool with actual software professionals.

Read Bio-inspired active sensing using reinforcement learning

Bio-inspired active sensing using reinforcement learning

Scientific Computing, Machine Learning

Explore how reinforcement learning can drive sensory-motor integration in distributed systems inspired by the whisker barrel cortex, training on images with movable sensors, and potential 3D object recognition.

Read Benefit points - what will it take for IT professionals to use them

Benefit points - what will it take for IT professionals to use them

Software Engineering

Just as story points are estimates of the cost of a piece of IT functionality, benefit points are estimates of the intended benefit (value for stakeholders) of that piece of functionality. It seems obvious that one should use benefit points in addition to story points, but benefit points (or similar metrics) are not in widespread use.

Read Benchmarking Partitioning tools for Supercomputers

Benchmarking Partitioning tools for Supercomputers

Scientific Computing, Machine Learning

How can we make best use of partitioning software and distribute workloads among compute nodes in a supercomputer?

Read Benchmarking Modern AI Hardware for Natural Language Processing

Benchmarking Modern AI Hardware for Natural Language Processing

Machine Learning

A new generation GPUs and AI accelerators such as IPUs promise massive speedups for NLP. Do they work out in practice?

Read Autonomous Self-healing Software Systems

Autonomous Self-healing Software Systems

Software Engineering, Machine Learning

Investigate, develop and evaluate data-driven techniques and prototypes that help software engineers build software systems that are autonomously self-healing. These are systems that can understand when they are not operating correctly and, without human intervention, make the necessary adjustments to restore themselves to normal operation.

Read Automatic detection of abnormal video events in sport videos

Automatic detection of abnormal video events in sport videos

Machine Learning

Use machine learning and video processing techniques to automatically find events in sports videos. For example, in football, some "easy" ones are goals, but others like tackles are harder.

Read AI-based virtual avatar for police interview training

AI-based virtual avatar for police interview training

Machine Learning

We are developing an AI child avatar for the interview training of the police officers to protect vulnerable children from abuse.

Read Adaptive Tests for Memory Training using Asymmetric Search Point Location

Adaptive Tests for Memory Training using Asymmetric Search Point Location

Machine Learning

Memory training exercises are known to have a positive effect on improving the memorability of humans. A memory training task can be as simple as trying to remember a password of increasing complexity or a number of varying length.

Read A system for planning and analyzing crisis management exercises

A system for planning and analyzing crisis management exercises

Software Engineering

Crisis response exercises are held regularly, but often with unclear learning objectives, unplanned data collection and inferior analyses. You will contribute to developing an exercise management system for structured planning, execution and analysis of crisis response exercises.

Read A Jira extension for Benefits Management in IT-projects

A Jira extension for Benefits Management in IT-projects

Software Engineering

It is important for IT development projects to estimate and keep track of the benefit of the software they are producing. You will help develop tools for this purpose.