We are looking for an excellent, creative, and highly motivated scientist with a MSc or equivalent in computer science, network science, statistical physics, applied mathematics, data science, computational social science or related fields. The candidate is going to work in the data analysis of multi-attributed online social networks for understanding the emergence of intersectional inequalities and biases in network-based algorithms. The project is funded by a EU Horizon Europe grant (Multi-Attribute, Multimodal Bias Mitigation in AI Systems, Grant ID: 101070285) and implemented in close collaboration with other research organizations that are aiming for socially responsible AI solutions.
This is a 3-year PhD position to work with Fariba Karimi [1] in the Computational Social Science and Network Inequality team at the Complexity Science Hub Vienna, Austria [2]. The successful candidate will play a leading role within this funded project, designing, managing, executing, and publishing research in collaboration with other researchers within this project and elsewhere. You will work in close collaboration with network scientists, physicists, computer scientists, and social scientists to analyze multi-criteria fairness in network-based algorithms and to develop intervention and mitigation methods.
Please send your application material to [email protected] with the subject line “PhD Fairness in Networks”. The application must include:
- a curriculum vitae
- a list of publications
- a brief research statement (why you think you are an excellent candidate in this topic and what research you would like to do with us)
- any additional material that helps us to understand that you are research-oriented, technically skilled, and creative
- names and full contact addresses of at least two individuals who are willing to write a letter of recommendation for you if we request it.
We will start evaluating applications immediately. The call remains open until the position is filled. CSH is committed to the principle of equal employment opportunity for all applicants. All employment decisions are therefore based on job requirements, qualifications, merit, and organizational needs. We strongly encourage individuals from underrepresented groups to apply. We process your personal data in accordance with the law (https://www.csh.ac.at/data-protection/).
More info: https://www.csh.ac.at/wp-content/uploads/2022/11/CSH_Job_PhD_MULTI_CRITERIA_FAIRNESS_IN_NETWORKS.pdf