Job board

We at KTH AI Society strive to bridge the gap between our members and the industry. It’s quite simple, companies working for the solutions of tomorrow need the talent of today. So below we listed all relevant work opportunities for you to take on new challenges.

For more opportunities, visit our strategic partner, Stockholm AI.

If you want to make a job posting contact us at jobs@kthais.com.

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Paid Internship and Master Thesis

🌍 Snappet, Utrecht in the Netherlands or remote

Master thesis

Master thesis and internship.

Snappet is a company transforming primary education. Using smart classroom technology, we managed to increase learning outcomes (scientifically proven) in thousands of primary schools. Part of the benefit is that the platform saves teachers almost an hour a day by removing the workload of correcting answers and finding adequate exercises for pupils. Other improvements are algorithmic-driven, using data to provide insights to teachers and to tailor the experience of the pupils. Research on the algorithms is important, and Snappet will actively support interns with an internship compensation, extensive mentorship, readily available data and state-of-the-art computing resources.

The research will take place in the related domains of knowledge tracing (keeping track of the pupils’ learning), performance prediction (being able to predict the (in)correctness of the answer of a pupil on a given question) and personalization (being able to decide what content fits best for a pupil or classroom at any given time given their state). As such it brings together recent improvements from the machine learning domain to the educational data mining area.

As a scale-up, Snappet is currently active in the Netherlands, Spain and the US. The office is located in Utrecht but we can easily facilitate online-only internships. There are 100-200 people working at Snappet, and around 14 of those remain involved in researching and engineering our algorithms. We have more than 300 000 pupils working with Snappet during their school day (most on a daily basis), who together answer more than 15 million questions a day. This is more than enough data to create impactful machine learning and deep learning approaches for pupil learning.

What are we looking for: - Applicants with a data background and who are enthusiastic about improving education

  • Preferably applicants that want to write their master thesis as part of their last year in a Machine Learning related master. We welcome applicants willing to begin their internship part-time in the fall of 2022, and then move to full-time as their master thesis starts in late 2022 or early 2023.

  • Applicants need to be fluent in python and be experienced with important datascience packages (pandas, numpy, matplotlib, tensorflow, pytorch). Experience with SQL, parallel processing, (AWS) cloud computing, recommendation systems, knowledge tracing algorithms, matrix factorisation, reinforcement learning or transformer networks are all considered a significant plus.

What we offer: - Research in an area with direct societal impact

  • Mentorship by our data scientists and machine learning engineers

  • The possibility to write your master thesis as part of your internship.

  • Unique opportunity to work with big data in a medium-sized company

  • An internship compensation

Ask questions to last years intern Nino at: segala@kth.se

Powering E-Commerce with ML & AI

🌍 Asket, Stockholm

Master thesis

ASKET is a direct-to-consumer clothing brand on a mission to slow down fashion and end over-consumption by creating garments free of compromise, allowing more people to live with fewer but better items. Aside from creating zero compromise garments, a huge part in the success of a modern e-commerce based retailer is to consolidate, manage and act on the data that is being collected from multiple touchpoints.

ASKET has a modern data infrastructure built in order to support automation and data-driven decisions which in short consists of a cloud computing-based data warehouse (DWH) and a customer data platform (CDP). This infrastructure yields datasets which comprise web-interactions, cart creations, transactions and size-related data.

Given these datasets we are now looking to explore how ML can further be used in order to provide best of breed e-commerce. As an example, during last year we developed and launched our proprietary ML-based (SVM) Size Finder with the ambition to increase customer trust and reduce costly and emission driving returns and exchanges. During spring 2022 we are looking for 1-2 students who are looking to explore the latest ML algorithms using highly real and applicable data as their thesis project. Some (not exclusively) of the fields that are of interest are...

  • Customer Loyalty, Retention Modeling & Churn Prevention.
  • Purchase Propensity Modeling.
  • Recommendation Engines.
  • Size Finder 2.0 - Size Recommendation Algorithm.
  • Demand forecasting, production planning & stock optimization.

Applications are open until November 30th and interviews will be held continuously. Send CV along with some words about what area you think sounds interesting to vidar@asket.com and we'll meet for some coffee and a chat at our HQ at Odenplan.