We are always looking for students to join us in our research projects. We are specifically looking for students (PhD, Honours, Masters, or other types of projects) in the following projects:
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PhD Scholarship: AI-Driven Dementia Risk Assessment
Join an international research team to develop explainable AI models for dementia risk prediction and contribute to tools that could transform clinical practice.
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Design of new proteins fit for industrial applications using machine-learning and co-evolutionary frameworks
The Mercadante Group and our lab is seeking an exceptionally motivated individual to join as a PhD candidate in protein design and discovery of new proteins fit for industrial applications. In particular, the candidate will explore the design and testing of recombinant proteins by means of a variety of computational workflows involving machine learning, molecular…
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Auditing Artificial Intelligence with Adversarial Learning
We aim to design and develop new methods to attack machine learning models and use the adversarial attacks to define a measure of reliability. Weak performances of models where data sets are not representative or flaws in training process are a common issue in Machine Learning. This leads to misclassification and unfairness of the model.…
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Predicting Persistence of Environmental Pollutants
Most chemicals that are currently produced sooner or later end up in the environment, many of them in rivers and other waters. It is essential to know their fate in terms of transformations and persistence. Harmful chemicals that degrade quickly might pose no big thread to the environment, however persistent toxic compounds can have lasting…
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Design for Degradability – In-Silico Development of Sustainable Chemicals
An important aspect in the development of novel chemicals is their environmental fate, that is their ability to degrade when released in the environment. To achieve this, the goal is to design compounds that fulfill a certain function – for example medication or pesticides, and at the same time allow for quick degradation into harmless…
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Adversarial Time Series
Adversarial Machine Learning is a field of Machine Learning that focuses on exploiting model vulnerabilities by making use of obtainable information from the model. Studying a model’s weaknesses to adversarial attacks not only helps the researcher understand more about the model itself, but also allows them to defend against malicious attacks and prevent potentially fatal…
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Do Neural Networks Pay Off?
For a while now, we have seen the trend that neural networks are vastly popular, and a large portion of the machine learning research is dedicated to achieving minor gains in accuracy at huge power costs. We hypothesize that, given the same love and care (in terms of nifty pre-processing strategies etc.), traditional machine learning…
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Image Compression to Support Image Processing
This project aims to investigate the potential benefits of using our newly developed image compression technique, based on multivariate trees, to enhance image processing machine learning models. The objective is to explore whether employing this technique can lead to faster and more efficient training of these models, requiring fewer iterations, layers, and parameters. While previous…