Projects in the CompSci doctoral programme
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.
