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Research Fellow in Cultural Data Analytics

Tallinn University - CUDAN ERA Chair project

Location: Tallinn - Estonia
Salary: Not Specified
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 29th April 2021
Expires: 31st May 2021

Start of the employment contract: 01.07.- 01.09.2021, duration of the contract is up to 31.12.2023. Deadline of submitting the application documents is 31st May, 2021.

 Successful candidates will join the CUDAN ERA Chair project in Cultural Data Analytics, which is funded by the European Commission in the Horizon 2020 research and innovation program with 2.5 million Euro (Grant no. 810961). The selected fellows will complement a highly multidisciplinary research group, currently consisting of 4 faculty, 4 senior fellows, and 5 PhD Students. For more information regarding our mission, group members, and ongoing events see

Requirements for the candidate (incl professional experience)

- A PhD in a computational or quantitative area, such as computer science, information science, network science, physics, or mathematics, while demonstrating understanding or meaningful interest in socio-cultural phenomena. Alternatively, a PhD in a cultural research area, such as art history, computational linguistics, digital humanities, with a strong track record in computation or quantification.

- Demonstrated ability to produce (potentially) high-impact research and work with large-scale (socio-cultural) data, including corpora of visual and audiovisual materials, or capturing the structure and dynamics of multidimensional spaces of (cultural) meaning.

- Either strong skills in audiovisual machine learning, in at least one of the following areas: Computer vision, deep learning, or pattern recognition; image segmentation & feature classification regarding objects, scenes, faces, poses, textures, etc. (aka iconography); 2vec or embed-everything approaches; latent-space cartography; multidimensional data analysis & visualization (manifold learning, diffusion maps, etc.); or another meaningful state-of-the-art application of machine learning that can be useful to make sense of large-scale visual or audiovisual data.

- Or strong quantitative and computational skills, in at least one of the following areas: Data science, information science, or computational social science; socio-physics or reality mining; complexity science or network science; multilayer and temporal network analysis; higher-order graphs or topological data analysis; mathematical modeling (including ecology or socio-cultural dynamics); matrix cluster analysis (as found in network neuroscience, DNA microarray-analysis, or systems biology); multidimensional flow analysis or fluid dynamics; or another meaningful state-of-the-art application of computation and quantification that can be useful for making sense of cultural dynamics.

Desired skills

– Experience in the acquisition and processing of large (cultural) datasets, including familiarity with data dumps, APIs, scraping, streaming, knowledge graph queries, and data integration.

– Advanced programming skills in at least one widely used language (e.g. Python, R, Julia, Processing, Javascript/D3, C++, or equivalent), including proficiency with libraries for data manipulation and analysis, machine learning, etc.

– Strong visual literacy and data visualization skills. Ability to read and produce high-quality scientific figures as found in multidisciplinary journals. Designing dynamic visualizations and interactive experiences is a plus.

– Preference will be for candidates who possess multidisciplinary competence and the necessary open-mindedness to bridge the so-called two worlds, where understanding implies qualification of specific complications and quantification of emerging complexity.

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* Salary has been converted at the prevailing rate on the date placed
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