Read the list of projects to choose from when applying for the CompSci programme. You will also find the names of the supervisors dedicated to each project. This is a unique possibility to work with top level researchers in their fields of expertise.
NB! None of the projects are currently open.
Call 1 projects were opened in 2020, with application deadline in the beginning of 2021, and the start of the doctoral programme for Call 1 projects was autumn 2021. Call 2 projects were opened in 2021, with application deadline in the beginning of 2022, and the start of the doctoral programme for Call 2 projects was autumn 2022.
Astronomy
Project span computational cosmology and observational and computational studies of the sun
Call 1: Projects starting autumn 2021
- Massive parallelization of end-to-end CMB analysis codes
Supervisors: Hans Kristian Eriksen, Ingunn Kathrine Wehus - Simulations of galaxy formation: interplay between baryonic feedback and dark matter models
Supervisors: Sijing Shen, Claudia Cicone
Call 2: Projects starting autumn 2022
Bioscience and AI
Projects focus on computational and experimental neuroscience, addressing the molecular mechanisms of learning and the interplay between biological and artificial learning systems.
Call 1: Projects starting autumn 2021
- Bio-inspired neural networks for navigation
Supervisors: Anders Malthe-Sørenssen, Gaute T. Einevoll - Large-scale recordings of neurons to reveal mechanisms of learning and memory
Supervisors: Marianne Fyhn, Anders Malthe-Sørenssen - Large-scale network simulations of mouse visual cortex
Supervisors: Gaute T. Einevoll, Marianne Fyhn - Modelling systems levels changes in brain aging induced by genome instability
Supervisors: Hilde Nilsen, Gaute T. Einevoll
Call 2: Projects starting autumn 2022
- Neuron population dynamics and the role of neuromodulators for learning in biological and artificial neural networks
Supervisors: Marianne Fyhn, Anders Malthe-Sørenssen - Neural basis of complex memory processing - common challenges in brain and AI
Supervisors: Marianne Fyhn, Anders Malthe-Sørenssen - Bio-inspired methods for continual learning in deep neural networks
Supervisors: Kai Olav Ellefsen, Mikkel Elle Lepperød - Causal learning in neural networks and the brain
Supervisors: Anders Malthe-Sørenssen, Mikkel Elle Lepperød
Call 2b: Project starting winter 2022/2023
Chemistry
Computational and experimental projects at the Hylleraas center for computational quantum mechanics and in the science and technology of catalysis.
Call 1: Projects starting autumn 2021
- Acceleration of Many-Electron Attosecond Dynamics Simulations
Supervisors: Thomas Bondo Pedersen, Simen Kvaal - Catalyst Discovery by Combining Computational Chemistry with Machine Learning
Supervisors: David Balcells, Riccardo De Bin - Computational modelling of reaction mechanisms involving metal organic frameworks
Supervisors: Ainara Nova, Unni Olsbye - Development and implementation of multi-resolution models in the exa-scale
Supervisors: Michele Cascella, Thomas Bondo Pedersen - Kinetic measurements, atomistic and kinetic modelling of reactions in confined space
Supervisors: Unni Olsbye, Stian Svelle
Call 2: Projects starting autumn 2022
- Ab initio molecular dynamics (MD) for accurate descriptions of entropy and diffusion in nanoporous catalysts
Supervisors: Stian Svelle, Michele Cascella - Development of density-functional methods utilizing tensor densities
Supervisors: Erik Tellgren, Trygve Helgaker - Mechanistic study of CO2 hydrogenation reactions using microkinetic modelling
Supervisors: Ainara Nova, Mats Tilset - Molecular noninteracting kinetic energy by machine learning
Supervisors: Trygve Helgaker, Simen Kvaal - Operando studies of porous catalysts and reaction mechanisms
Supervisors: Stian Svelle, Silvia Bordiga
Geoscience
Projects span geophysics, climate research, and geological processes and include traditional computational methods and machine learning based projects.
Call 1: Projects starting autumn 2021
- Computational modelling of hydrogen diffusion along slip planes in upper mantle silicates
Supervisors: Razvan Caracas, Clinton Phillips Conrad - Incorporating real-time datastreams in modelling the state of the Arctic cryosphere
Supervisors: Andreas Kääb, Thomas Vikhamar Schuler - Modelling microscale atmospheric turbulence in the surface layer
Supervisors: Terje Berntsen, Nikki Vercauteren - Role of anisotropic viscosity for computational modelling of convection in the Earth’s mantle
Supervisors: Clinton Phillips Conrad, Ágnes Király - Variable mesh Earth System Models on cloud platforms for high latitude volcanic eruptions
Supervisors: Kirstin Krüger, Trude Storelvmo
Call 2: Projects starting autumn 2022
- Mesoscale modelling of plastic instabilities using machine learning
Supervisors: Luiza Angheluta, Anders Malthe-Sørenssen - Modelling impact of melts on mantle diffusion and viscosity with geodynamic implications
Supervisors: Razvan Caracas, Carmen Gaina - Evaluating mechanisms for intraplate volcanism using the observed distribution of seamounts
Supervisors: Carmen Gaina, Clinton Phillips Conrad - Molecular scale machine-learning based modeling of dynamic fracture in rocks
Supervisors: Anders Malthe-Sørenssen, Henrik Andersen Sveinsson - Optimal Climate
Supervisors: Joseph Henry Lacasce, Morten Hjorth-Jensen - Wavelet-based scale estimation of turbulent phenomena in the ocean and atmosphere
Supervisors: Pål Erik Isachsen, Trude Storelvmo - Predicting laboratory earthquakes using machine learning
Supervisors: François Renard, Benoit Cordonnier
Call 2b: Project starting winter 2022/2023
Mathematics and Statistics
Projects span a broad range of mathematical and statistical subjects – all with a focus on machine learning or broader data science methods.
Call 1: Projects starting autumn 2021
- Deep reinforcement learning for industrial applications: taking flow control to the real world
Supervisors: Atle Jensen, Jean Rabault - Statistical learning method for chemistry applications
Supervisors: Riccardo de Bin, David Balcells - Utilizing covariate information in recommender systems
Supervisors: Ida Scheel, Arnoldo Frigessi
Call 2: Projects starting autumn 2022
- Backtracking gradient descent-based algorithms to defend DNNs against adversarial attacks
Supervisors: Tuyen Trung Truong, Anders Christian Hansen - Stable representations in deep learning
Supervisors: Miroslav Kuchta, Kent-Andre Mardal, Mikkel Elle Lepperød - Deep learning observables of solutions of nonlinear hyperbolic partial differential equations
Supervisors: Ulrik Skre Fjordholm, Vegard Antun
Physics
Computational and machine learning projects across several fields of physics spanning quantum mechanics, biological physics and nano science.
Call 1: Projects starting autumn 2021
- Frictional properties of surface structures generated by machine-learning
Supervisors: Anders Malthe-Sørenssen, Morten Hjorth-Jensen - Machine-learning-based molecular modelling of nanoscale geological processes
Supervisors: Anders Malthe-Sørenssen, Morten Hjorth-Jensen - Mesoscale modelling of turbulence and swarming behavior in soft active matter
Supervisors: Luiza Angheluta, Anders Malthe-Sørenssen - Measurement and mechanistic modelling of 3D cell migration
Supervisors: Dag Kristian Dysthe, Anders Malthe-Sørenssen - Development of Quantum Computing Algorithms for studies of quantum mechanical many-body systems
Supervisors: Morten Hjorth-Jensen, Simen Kvaal
Call 2: Projects starting autumn 2022
- Deep-learning based analysis of stem cell differentiation pathways
Supervisors: Hanne Scholz, Dag Kristian Dysthe - Measurement and mechanistic modelling of 3D cell migration
Supervisors: Dag Kristian Dysthe, Anders Malthe-Sørenssen - Mesenchymal stem cell differentiation and mineralization in biomimetic hydrogels: microfluidics and modelling
Supervisors: Dag Kristian Dysthe, Luiza Angheluta - Designing materials for sustainable energy applications using machine learning
Supervisors: Anders Malthe-Sørenssen, Henrik Andersen Sveinsson - Development of Quantum Computing Algorithms for studies of quantum mechanical many-body systems
Supervisors: Morten Hjorth-Jensen, Simen Kvaal
Supervisors
The CompSci programme provides a broad list of experienced supervisors on a top international level, who has track records in interdisciplinary research and experience in combining computational and disciplinary approaches in their research.
