PAID Master’s Thesis in Machine Learning for Mental Health

The Aalto University Department of Computer Science is seeking a master’s student to work on machine learning on individual-level data for mental health. This research-oriented project focuses on analyzing the data from a psychiatry study, which has collected data from patients as well as healthy controls. The main goals are to determine the best methods to distinguish between patients with mental disorders and healthy controls. Part of this work will be finding the features that are most informative to discern between the two groups. Data comes from a variety of different sources, including mobile phones, physical sensors, and questionnaires.

This work will entail reviewing literature, data cleaning and preprocessing, working with different types of data (time series, location data, etc.), and creating a data-analysis pipeline. The successful applicant must have hands-on knowledge with machine-learning methods and be willing to learn about the domain (psychiatry). The thesis is expected to be completed within 6 months and the aim is to publish the research outcome as a scientific paper.

Requirements: Hands-on experience with machine learning (multiple methods known at some level, ability to independently learn more), excellent Python skills.

Advantageous: experience with databases like SQL/MySQL, familiarity with python libraries such as scikit Learn, Pandas, Numpy, Scipy, experience with scientific programming tools: git, scripting, Jupyter.

In order to apply please send your CV together with a short description of why you are interested in this project and why you are a good candidate to talayeh.aledavood@aalto.fi. Please also include a list of relevant courses and past projects describing the data analysis/machine learning techniques and tools used.

Supervisor: Prof. Aris Gionis

Instructor: Postdoctoral Researcher Talayeh Aledavood