Join us
We always have many exciting opportunities to join our group as research student, giving you the opportunity to work in interdisciplinary teams with international collaborators. Below is a (incomplete) list of projects that are currently actively looking for someone. Or just directly contact our group members if you are interested in one of our research areas.
Postgrad student for the project “Algorithms and Applications for Boolean Matrix Factorization”
Summary The goal of a Boolean matrix decomposition (BMD) is to represent a given Boolean matrix as a product of two or more Boolean factor matrices. It is a well-known and researched problem with a wide range of applications, e.g. in multi-label classification,...
PhD position in Spatio-Temporal Data Mining
Summary Spatio-Temporal Data Mining is an emerging research area under the concept of smart city and smart nation. It covers a wide range of research problems, including geospatial topic mining, trajectory mining, spatial region analysis, user mobility modeling and...
Postgrad students for the project “Deep Generative Models for Anomalous GPS Trajectory Detection”
Summary With the availability of large-scale GPS trajectory data, automatically detecting anomalous trajectories has become a critical concern in many real-world scenarios. For example, taxi drivers may take unnecessary detours to overcharge tourists. The main...
Student project or summer scholarship – Adversarial learning to identify bias in data sets
Summary Adversarial learning aims to identify weaknesses in machine learning models. The goal is to identify potential problems that cannot be found using traditional evaluation using test sets. It has been used successfully in a wide range of applications,...
Summer scholarship or student project – Computational framework for evaluating identity of engineered cell types
Summary Motivation Since the breakthrough discovery in 2006 that living cells can be “reprogrammed” (subject to specific biochemical stimuli) from one to another cell type, cell reprogramming protocols have been optimized to meet the need for essential cell types...
Postgrad student for the project “Machine Learning-based Prediction of Biodegradation Persistence”
Summary The prediction of the biodegradation processes of environmental pollutants is an important task for the regulation of chemicals and therefore for the chemical industry. An important task in this process is the prediction of the persistence of chemicals in...
Student project – Confidentiality methods in official statistics
Summary Statistical disclosure control (SDC) methods, like random rounding, are commonly used by official statistics organisations (including Stats NZ Tatauranga Aotearoa) with the goal of preventing individuals or organisations from being identified. Our project...
Postgrad student for the project “Identififying and analysing bat calls”
Summary Our goal is to use machine learning methods to identify patterns in large bat call data sets. The bat calls are recorded by a network of sensors that are set up in forests and near rivers. They record sounds at the frequencies of bat calls, producing...
Postgrad student for the project “Machine Learning approaches for mass spectrometry data analysis”
Summary A wide range of Computational Sustainability applications, including biodegradation pathway prediction and sustainable drug development, rely on experimental data generated with analytical techniques such as mass spectrometry (MS). While mature tools for...
Summer scholarship or student project in Adversarial Machine Learning
Summary Adversarial learning aims to identify weaknesses in machine learning models. The goal is to identify potential problems that cannot be found using traditional evaluation using test sets. It has been used successfully in a wide range of applications,...
