Funded Master Thesis in Probabilistic Machine Learning group

Deadline: 1 October 2018

The Probabilistic Machine Learning group (PML) at Aalto University is looking for a master student to work on a challenging machine learning problem. The position is fully funded and it is filled as soon as a suitable candidate is found. Note that, it is also possible for students, who are not yet in their MSc thesis stage to apply.

If you are interested, please send an email to contact addresse below attaching your CV, study records, and a brief statement (max. 1 page) describing your qualifications for this position including previous experiences in machine learning and programming skills.

The ideal candidate should be able to contribute on both theory and application sides of the project. This includes design and implementation of new algorithms, working with real data, and writing research papers, which are valuable experiences for a future doctoral position and/or an industry career in data science.

Title: Application of machine learning algorithms on marketing automation

Abstract: Hidden markov model (HMM) is a statistical model, in which the observations are dependent on latent variables which assumed to be from a markov process with unobserved states. HMMs are widely used to model different stochastic processes in variety of applications such as speech processing, bioinformatics, and marketing. In this project, a marketing problem is modeled as a HMM, where parameters of the system are unknown and needed to be estimated. The student is expected to perform a comprehensive literature review on the state-of-the-art methods of the aforementioned problem to implement and comparatively test their performance on the given database.

Keywords: Machine learning, Hidden Markov Model (HMM), Parameter estimation, Marketing automation

Contact person: Neda B. Marvasti (neda.marvasti [at] aalto [dot] fi)

Supervisors: Prof. Samuel Kaski