Assistant / Student Worker /HiWi in Interactive Visual Data Analysis
We are looking for a motivated student (m/f/d) to be a student assitent (HiWi) in the areas of visual analytics, interactive data science, and interactive machine learning in the Interactive Visual Data Analysis Group at the University of Zurich (UZH). As part of the group, you will help develop/implement new algorithms and techniques in our group framework. The overall goal to help develop approaches for characterization, design, and evaluation of interactive visual interfaces to combine the strengths of both humans and algorithms in interactive machine learning and data science applications.
Research Context of the IVDA Group
Our primary research focus is at the intersection between Information Visualization, Visual Analytics, Human-Computer Interaction, and Machine Learning. Your support is necessary to help the group follow a human-centered approach to data science, in order to foster the involvement of humans in the data analysis process with interactive visual interfaces. Your implementations will help to combine different strengths of humans and machines in an iterative and incremental data analysis process in order to tackle remaining data science challenges:
- Examples for data-oriented challenges are heterogeneous data, dirty data, uncertain data, or unlabeled data.
- Important model-oriented challenges include data pre-processing, model building, model quality assessment, or model explanation.
- Particularly interesting user-oriented challenges are different degrees of user expertise, users’ personalization intents, and understanding and supporting user preferences with respect to data and tasks.
For more information about my recent research context, see juergen-bernard.de
- Knowledge or interest in one or more of the following: information visualization, visual analytics, machine learning, data mining, information retrieval, or related data science fields.
- Profound skills in programming (Python, Java)
- Interest to work on applied research questions in a collaborative research environment
How to apply
Applications should include:
- Short informal motivation statement
- CV, certificates of study/educational background
- Exposition of prior data visualization experience
- Your expectations to the position, skills you want to learn