The call for 3-month summer intern positions for the summer of 2021 (for the students of University of Helsinki and other Finnish Universities) have not yet been published! 

Atmospheric AI

In this project we will study the application of these methods in physical domains in collaboration with substance area experts in meteorology and/or atmospheric physics and chemistry with focus on understandability and interpretability of the methods. The project will be done in collaboration with the Institute for Atmospheric and Earth System Research (INAR). In this position an interest and background in natural sciences is considered an advantage. 

Open source tools for randomization and exploratory data analysis

Visual exploration of high-dimensional datasets is a fundamental task in exploratory data analysis (EDA). We have developed a theoretical model for EDA, where patterns already identified and considered known by the user are input as knowledge to the exploration system. The user is hown views of the data where the user’s knowledge has been taken into account. Based on our recent work in EDA and randomization methods, the tasks in this project are twofold.

Implement an open-source tool for exploratory data analysis. The tool should be web-based, cross-platform, and scale to large datasets. Develop an open source library (e.g., in R, Python, JavaScript) implementing modern randomization methods for the use of data mining. Examples of such randomisation techniques include for instance maximum entropy models and different constrained randomisation schemes.

These tasks require good programming skills. Previous experience of open-source software development is considered an advantage.