Hi Master students of Machine Learning, Computer Science, Computational linguistics or something similar!
Up for writing your Master’s thesis? These are the project suggestions we offer for January 2018!
You need your skills, a strong will to grow and develop, and a passion for music. You also need to be on the last year of your studies and able to start writing your thesis starting in January 2018.
These suggestions for master thesis projects are paid work, and they can be adjusted to your skillset and the university demands. This is a special chance to dive deep into some real challenges with one of our teams.
Machine learning applied to music search
There are several parts in our search platform that use machine learning to give the best user experience possible. We want a master’s student to look into the best way of doing this. (Team Search Platform)
Machine learning applied to personalized daily playlist
We’d be thrilled if a sharp master’s student took a stab at how machine learning can be applied on creating personalized daily playlists. You will get to explore our state of the art music recommendations of the songs a user is most likely to play, state a hypothesis, implement it, and and then verify it with real users. (Team Market Opportunities)
Natural Language Understanding applied to music search
We are looking for a master’s student with a major in Natural Language Processing (or similar) up for writing a master’s thesis on how Natural Language Understanding can be applied to music search. (Team Quest)
Modeling data sets and artificially generated data
We are looking for a master’s student who wants to write a master’s thesis on modeling data sets and artificially generated data. It will be great if you have taken generative models courses and put that knowledge to use before. (Team Data mission)
Personalisation of the checkout experience
Come here and write a master’s thesis on personalisation of the checkout experience. You will get to apply state of the art machine learning on real world data to explore an hypothesis, implementing and verifying a prototype on real user interactions. (Team Iron Bank)
Machine learning applied on user subscription
Are you into huge amounts of data? We’d like a master’s thesis on applying machine learning algorithms on massive data sets, to identify users that are likely to cancel their Spotify premium subscriptions. If you have the will and the skills, we have all the data you need! (Team Consumer subscription)
Using Artificial intelligence or Machine learning in Customer Systems
Come help us explore how to best use technology like artificial intelligence, machine learning, smart assistants and bots or UX, in Customer Systems. (Team Customer Systems and Tools)
Models for managing risk in code changes
Come help us figure out which parts of the code are most problematic when it comes to making changes. Based on the data we collect from Continuous Integration, your thesis will define the right model to decide how “dangerous” a change is and how likely it is to fail. (Team Client Build)
Make sure to specify what thesis suggestions you’re interested in our application form, and we will try to match you with the best thesis project for your skillset. Keep in mind that the suggestions is just a first draft and might change until you start in January 2018.
All these projects will be run in Stockholm and we will pay you 35 000 SEK for your thesis (note that we can’t cover things like relocation, housing, or travel expenses).
These master thesis opportunities are only open to students that are currently studying at a Swedish university or campus .
When you apply we ask you to fill in a quick application form, attach a resume and a cover letter. In your cover letter, please include why the thesis suggestions you chose are interesting and relevant to you. You can also add your own thesis idea if you have one. Our Spotify Recruitment team will get back to you no later than the end of November 2017.
Applications close on October 15th.
We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.