- Corpora - ELRA lists

Second call for TextDetox CLEF-2024 Participants
by Daryna Dementieva 29 Apr '24

29 Apr '24

Dear all, Our shared task on *multilingual text detoxification* ( https://pan.webis.de/clef24/pan24-web/text-detoxification.html) is ongoing and reaching *its final phase*😉 We are releasing the parallel pairs for the dev part: https://huggingface.co/datasets/textdetox/multilingual_paradetox and new toxic sentences for *the test part*: https://huggingface.co/datasets/textdetox/multilingual_paradetox_test Also, you can check out new baseline: new fine-tuned multilingual text detoxification model: https://huggingface.co/textdetox/mt5-xl-detox-baseline We are waiting for you submission here: https://codalab.lisn.upsaclay.fr/competitions/18243 *till May 12th*🤗 You can submit for *ANY** language*! There are 9 of them: English, Spanish, German, Chinese, Arabic, Hindi, Ukrainian, Russian, and Amharic. All kind regards, Daryna Dementieva on behalf of TextDetox CLEF-2024 organizers

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CfP: 2024-2025 Bloomberg Data Science Ph.D. Fellowship
by Bloomberg Research Grant Program (BLOOMBERG/ 731 LEX) 29 Apr '24

29 Apr '24

Hello, Bloomberg is happy to announce an exciting funding opportunity for Ph.D. students. The seventh edition of the Bloomberg Data Science Ph.D. Fellowship Program invites Ph.D. students working in broadly-construed data science to apply for fellowships. Our fellowship program, launched in 2018, provides the opportunity for outstanding Ph.D. candidates to be funded for up to three years of their Ph.D. studies to work on their research proposal. The recipients will collaborate and be supported by our Data Science community throughout this time and will complete 14-week summer internships with Bloomberg for the duration of their fellowships. Previous recipients of the fellowship are presented here: 2022-2023, 2021-2022, 2020-2021, 2019-2020, 2018-2019. Applications for the 2024-2025 academic year must be submitted by May 30, 2024. Fellowship recipients will be announced by July 15, 2024. Full details about the fellowship, specific topics of interest for this year and application process can be found at: https://www.bloomberg.com/company/values/tech-at-bloomberg/data-science/aca… We would appreciate it if you can share this opportunity with interested parties. Please direct all questions and future communications to rdml(a)bloomberg.net. Bloomberg

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Funded NLP PhD at Inria Paris and Télécom Paris
by Maria Boritchev 29 Apr '24

29 Apr '24

Dear all, We have a PhD opportunity in NLP and computational linguistics about automatic analysis of human ability to collaborate in dyadic and group conversations, for educational applications: [ https://jobs.inria.fr/public/classic/en/offres/2024-07248 | https://jobs.inria.fr/public/classic/en/offres/2024-07248 ] . Though the offer description in the link is in French, we strongly encourage non-French speakers to apply as well! The offer is translated in English below. Prospective candidates are encouraged to get in touch with us as soon as possible. Looking forward to reading you, Maria Boritchev and Chloé Clavel ______________________________________ Automatic analysis of human capacity to collaborate during dyadic and group conversations, for educational applications. Context and scientific objectives Work on dialog using NLP and deep learning approaches for Dialog Act prediction or sentiment analysis integrates the conversational aspects by capturing contextual dependencies between utterances using recurrent neural networks (RNN) or convolutional neural networks (CNN) for supervised learning (Bapna et al., 2017). The inter-speaker dynamics has also recently started to be integrated. For example, in (Hazarika et al., 2018), intra-speaker dynamics is modeled using a GRU (Gated Recurrent Unit). Other ways to model a conversation in structures that are more complex than flat sequences of utterances are also investigated by leveraging hierarchical neural architectures (Chapuis et al., 2020) or by using graphs in the neural architectures (Ghosal et al., 2019). The conversational aspects and contextual dependencies between the labels are also modeled using sequential decoders and attention mechanisms for NLP-oriented Dialog Act classification (Colombo et al., 2020). Regarding neural architectures dedicated to generating an agent’s behavior, a few studies on affective computing attempt to integrate collaborative processes. The studies concern the generation of agent’s non-verbal behaviors related to social stances (Dermouche & Pelachaud, 2016) and Long-Short-Term-Memory (LSTM) architectures are used as a black box in order to model inter-speaker dynamics. Other studies that are not relying on neural architectures address the question of selecting the agent’s utterance or best dialog policy (ex. conversation strategies such as hedging or self-disclosure or extroverted or introverted linguistic styles) according to the user’s social behaviors (multimodal behavior in (Ritschel et al., 2017) and verbal behavior in (Pecune & Marsella, 2020)). In both studies, a social reward is built for reinforcement learning. A recent work investigates neural architectures (Bert model named CoBERT) trained on Empathetic conversations for response selection, but there is no option in order to select the level or the kind of empathy which is the most relevant (Zhong et al. 2020). While these existing neural architectures (convolutional, recurrent and transformer), for tracking a speaker’s state in conversations are extremely promising by modelling inter-speaker dynamics and the sequential structure of the conversation, the phenomena they are detecting are restricted to sentiment, emotions, or dialogue acts. What is still missing in the module dedicated to tracking the user’s state in modular conversational systems is the consideration of the collaborative processes as a joint action of the user and the agent to understand each other, maintain the flow of the interaction and create a social relationship. The aforementioned neural approaches are very effective, but they are not very data-efficient. There are many use cases where the amount of available data is not sufficient to be able to use these methods, particularly when it comes to deep learning; this is notably the case in educational contexts, where the data at stake is quite confidential, especially when children are involved, as the data is considered to be personal data and is therefore subject to GDPR (https://gdpr-info.eu/). Computational linguistics provide us with other approaches to the analysis of conversations, symbolic and logic-based. These approaches rely on small amounts of data and focus on specific phenomena, such as management of implicit implications/information in dialogues (Breitholtz, 2020) and various contexts (Rebuschi, 2017). Segmented Discourse Representation Theory (SDRT, Asher and Lascarides, 2003) is one of the most widely used frameworks for dialogue analysis used within both formal and neural approaches to dialogue. Another approach is to propose a hybridation of knowledge graphs for modelling social commonsense and large language models (Kim et al., 2023). The objective of the thesis is to investigate approaches that hybridize neural and symbolic models. The approaches will be dedicated to analysing and controlling the level of collaborations between participants in conversations (e.g., misunderstanding analysis and management) through their verbal expressions. We will focus on educational applications such as classroom dynamics & student engagement analysis and conversational systems for supporting students with difficulties, or learning social skills following the ethical guidelines defined in (1). (1) [ https://web-archive.oecd.org/2020-07-23/559610-trustworthy-artificial-intel… | https://web-archive.oecd.org/2020-07-23/559610-trustworthy-artificial-intel… ] (Breitholtz, 2020) Breitholtz, E. (2020). Enthymemes in Dialogue. Brill. (Asher and Lascarides, 2003) Asher, N. and Lascarides, A. (2003). Logics of conversation. Cambridge University Press. (Rebuschi, 2017) Rebuschi, M. (2017). Schizophrenic conversations and context shifting. In International and Interdisciplinary Conference on Modeling and Using Context, pages 708–721. Springer (Kim et al., 2023) Hyunwoo Kim, Jack Hessel, Liwei Jiang, Peter West, Ximing Lu, Youngjae Yu, Pei Zhou, Ronan Bras, Malihe Alikhani, Gunhee Kim, Maarten Sap, and Yejin Choi. 2023. SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 12930–12949, Singapore. Association for Computational Linguistics. Supervision : Thesis supervisor: Chloé Clavel, senior research, ALMAnaCH team, Inria Paris Co-supervisor: Maria Boritchev, associate professor, S2a team, Telecom-Paris

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Funded NLP PHD at University of Birmingham (UK)
by Venelin Kovachev 29 Apr '24

29 Apr '24

PhD opportunity in data-centric NLP, with potential topics such as Active Learning, Curriculum Learning, Multi-objective optimization, Dynamic Adversarial Data Collection, Synthetic data generation, Red-teaming for AI, and interpretability for Natural Language Processing. Position is open until filled. Prospective candidates are encouraged to get in touch to discuss topics prior to formal application. More information: http://tiny.cc/mzbwxz -- Dr. Venelin Kovatchev, PhD Assistant Professor University of Birmingham

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OSNEM Special Issue:AI in Online Social Networks: opportunities and challenges
by Andrea Passarella 29 Apr '24

29 Apr '24

------------------------------------------------------------------------------ CALL FOR PAPERS Elsevier Online Social Networks and Media Journal (OSNEM) Special issue on AI in Online Social Networks: opportunities and challenges Submission Deadline: Continuous submissions until July 31st, 2024 https://www.sciencedirect.com/journal/online-social-networks-and-media ------------------------------------------------------------------------------ Online Social Networks and Media are a fundamental component of everyday life and the use of AI technologies in OSNEM can further boost their role. The use of AI in online social networks offers great opportunities and, at the same time, raises several challenges. AI's ability to analyze vast amounts of data in real-time allows social media platforms to offer highly personalized experiences to users. The use of AI may raise concerns about ethical issues such as privacy, algorithmic bias, misinformation, etc., but AI can also be used for content moderation on social media to detect and remove harmful or inappropriate content, identifying and mitigating the spread of fake news. etc. The use of AI on OSNEM can promote the democratic processes by facilitating the dissemination of information and encourage political engagement. On the other hand, AI algorithms can create echo chambers, influence voting behavior and generate significant risks for democracy. AI-driven security measures can help to protect OSNEM users from fraud and privacy breaches but, malicious actors can also use AI to support their attacks. The exponential diffusion of generative AI adds novel dimensions to this landscape, on the one hand supporting novel forms of interactions spanning into the Metaverse, but on the other hand exposing vulnerable users to dramatic threats. The aim of this special issue is to push the state of the art in using AI in OSNEM, by presenting quantitative contributions that investigate the opportunities and challenges of using AI in Online Social Networks. Within this framework, topics include, but are not limited to: - Using AI in OSNEM for personalization, efficiency, and recommendations; - AI-based studies for analysis and modelling of information and opinion dynamics in OSNEM; - AI-based predictions based on OSNEM data analysis; - AI impact on OSNEM security, trustworthiness and privacy; - Generative AI in OSNEM; - AI and social networking in the Metaverse; - AI methodologies for large-scale OSNEM data collection and analysis - AI methods to safeguard OSNEM users (e.g., bot detection, toxic content identification, content moderation, echo chamber avoidance) - Case studies of AI application in OSNEM Online Social Networks and Media is a multidisciplinary journal for the wide community of computer and network scientists working on developing OSNEM platforms and services and using OSNEM as a big data source to mine, learn and model the (online) human behaviour. Manuscripts only based on questionnaires, even focused on the reported use of social media, are outside the scope of the journal. On the other hand, the journal welcomes papers which present analyses based on big data mined from social networks/media. ----------------------------------------------------------------------------- Schedule Manuscript submission deadline: continuous submission until July 31st, 2024 (*) First notification: two months after the submission Expected publication: papers are published a few weeks after acceptance. Guest Editors Marco Conti, IIT-CNR, Italy Andrea Passarella, IIT-CNR, Italy ------------------------------------------------------------------------------ Instructions for submission Manuscripts must not have been previously published nor currently under review by other journals or conferences. If prior work was published in a conference, the submitted manuscript should include a substantial extension of at least 35% novel contributions. In this case, authors are also required to submit their published conference articles and a summary document explaining the enhancements made in the journal version. The submission website for this journal is located at https://www2.cloud.editorialmanager.com/osnem/default2.aspx. Please select ''VSI:AI&OSNEM'' when you reach the ''Article Type'' step in the submission process. To ensure that all manuscripts are correctly identified, for consideration by the special issue, the authors should indicate in the cover letter that the manuscript has been submitted for the special issue on “AI&OSNEM”. (*) Manuscripts can be submitted continuously until the deadline. Once a paper is submitted, the review process will start immediately. Accepted papers will be published continuously in the journal (in the first issue available as soon as the paper is accepted). All accepted papers will be listed together in an online virtual special issue published in the journal website. For further information, please contact the guest editors at {m.conti,a.passarella} at iit.cnr.it

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Job opportunities: 8 Postdoctoral & doctoral positions with different areas of focus
by Mahlberg, Agnes Michaela 29 Apr '24

29 Apr '24

Dear all, I have just started a new position as Humboldt Chair in Digital Humanities at Friedrich-Alexander-Universität Erlangen-Nürnberg in Germany and I am looking for researchers with a range of interests and expertise in language, computing and the digital world. I currently have 8 jobs to offer at postdoctoral level or at doctoral level. If you are interested in an exciting position, please do read on. If you know of potential candidates, please do share widely! What are the jobs about? Join a team of researchers who will be tackling an ambitious programme of innovative research looking at various aspects of language in today´s digital world. Specific project strands will develop computational, corpus, and statistical methods and software, topic-focused projects will be in digital environmental humanities, digital literary and cultural history, digitally supported storytelling and creative writing. In your cover letter, please specify which of these focus areas you are applying for. Depending on your qualifications and experience there are different options of appointment. Type of positions PhD positions are for up to 3 years (65% or 100%) Postdoctoral positions are initially for 2 years (100%), with the opportunity for extension after successful completion of that period. For more information see: https://www.jobs.fau.de/jobs/doctoral-or-postdoctoral-researchers-in-digita… Application deadline 17 May 2024 How to apply I´m very happy to take informal enquiries at this email address. Please send your application to dhss-kontakt(a)fau.de<mailto:dhss-kontakt@fau.de> (in PDF format, as a single document). The application has to include a cover letter (stating the area of focus that you are applying for), an academic CV, and evidence of all relevant qualifications. The first round of interviews will likely take place in the week beginning 3rd June. All the best Michaela -- Professor Michaela Mahlberg https://michaelamahlberg.com/ Humboldt Chair in Digital Humanities Head of Department Digital Humanities and Social Studies (DHSS)<https://www.dhss.phil.fau.de/> Friedrich-Alexander-Universität Erlangen-Nürnberg<https://www.fau.de/> Werner-von-Siemens-Str. 61 91052 Erlangen, Germany Editor of the International Journal of Corpus Linguistics https://benjamins.com/catalog/ijcl Host of the Life and Language Podcast https://anchor.fm/michaela-mahlberg/ @MichaMahlberg<https://twitter.com/MichaMahlberg> https://www.linkedin.com/in/michaela-mahlberg/

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Edge Hill Corpus Research Group – Meeting #12
by Costas Gabrielatos 28 Apr '24

28 Apr '24

The next meeting of the Edge Hill Corpus Research Group will take place online (via MS Teams) on Thursday 25 April 2024, 2:00-3:30 pm (UK time). Registration closes tomorrow (Wednesday 24 April), 11 am. Attendance is free. You can register here: https://store.edgehill.ac.uk/conferences-and-events/conferences/events/edge… Topics: Corpus Methodology, Large Language Models Speakers: Sylvia Jaworska<https://www.reading.ac.uk/elal/staff/dr-sylvia-jaworska> (University of Reading, UK) & Mathew Gillings<https://www.wu.ac.at/ebc/about-us/team/mathew-gillings/> (Vienna University of Economics and Business, Austria) Title: How humans vs. machines identify discourse topics: an exploratory triangulation Abstract Identifying discourses and discursive topics in a set of texts has not only been of interest to linguists, but to researchers working across social sciences. Traditionally, these analyses have been conducted based on small-scale interpretive analyses of discourse which involve some form of close reading. Naturally, however, that close reading is only possible when the dataset is small, and it leaves the analyst open to accusations of bias and/or cherry-picking. Designed to avoid these issues, other methods have emerged which involve larger datasets and have some form of quantitative component. Within linguistics, this has typically been through the use of corpus-assisted methods, whilst outside of linguistics, topic modelling is one of the most widely-used approaches. Increasingly, researchers are also exploring the utility of LLMs (such as ChatGPT) to assist analyses and identification of topics. This talk reports on a study assessing the effect that analytical method has on the interpretation of texts, specifically in relation to the identification of the main topics. Using a corpus of corporate sustainability reports, totalling 98,277 words, we asked 6 different researchers, along with ChatGPT, to interrogate the corpus and decide on its main ‘topics’ via four different methods. Each method gradually increases in the amount of context available. • Method A: ChatGPT is used to categorise the topic model output and assign topic labels; • Method B: Two researchers were asked to view a topic model output and assign topic labels based purely on eyeballing the co-occurring words; • Method C: Two researchers were asked to assign topic labels based on a concordance analysis of 100 randomised lines of each co-occurring word; • Method D: Two researchers were asked to reverse-engineer a topic model output by creating topic labels based on a close reading. The talk explores how the identified topics differed both between researchers in the same condition, and between researchers in different conditions shedding light on some of the mechanisms underlying topic identification by machines vs humans or machines assisted by humans. We conclude with a series of tentative observations regarding the benefits and limitations of each method along with suggestions for researchers in selecting an analytical approach for discourse topic identification. While this study is exploratory and limited in scope, it opens up a way for further methodological and larger scale triangulations of corpus-based analyses with other computational methods including AI. ________________________________ Edge Hill University<http://ehu.ac.uk/home/emailfooter> Modern University of the Year, The Times and Sunday Times Good University Guide 2022<http://ehu.ac.uk/tef/emailfooter> University of the Year, Educate North 2021/21 ________________________________ This message is private and confidential. If you have received this message in error, please notify the sender and remove it from your system. Any views or opinions presented are solely those of the author and do not necessarily represent those of Edge Hill or associated companies. Edge Hill University may monitor email traffic data and also the content of email for the purposes of security and business communications during staff absence.<http://ehu.ac.uk/itspolicies/emailfooter>

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Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD 2024): Call for Participations
by Aaron Poet 26 Apr '24

26 Apr '24

Call4Participations: MWE-UD2024 Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD 2024): Call for Participations Colocated with: LREC-COLING 2024 <https://lrec-coling-2024.org/> (Torino, Italia) Date of the Workshop: May 25, 2024 Organised and sponsored by: The Special Interest Group on the Lexicon (SIGLEX <http://www.siglex.org/>) of the Association for Computational Linguistics (ACL <https://www.aclweb.org/portal/>), SIGLEX’s Multiword Expressions Section ( SIGLEX-MWE <https://multiword.org/organization/constitution.html>), Universal Dependencies (UD <https://universaldependencies.org/>) and UniDive <https://unidive.lisn.upsaclay.fr/> Cost Action CA21167. ------------------------------ Exciting News - Initial program available with invited speakers and accepted archival and non-archival papers. ------------------------------ Contents on this page - Keynote Speakers <https://multiword.org/mweud2024/#keynotes> - Accepted Papers <https://multiword.org/mweud2024/#accepted> - Description <https://multiword.org/mweud2024/#description> - Organizing Committee <https://multiword.org/mweud2024/#organizers> - Program Committee <https://multiword.org/mweud2024/#committee> - Sponsors and Support <https://multiword.org/mweud2024/#sponsors> - Anti-harassment Policy <https://multiword.org/mweud2024/#antiharassment> - Contact <https://multiword.org/mweud2024/#contact>

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Second CFP: 1st UniDive training Summer School 2024
by Atul K. Ojha 26 Apr '24

26 Apr '24

1st UniDive Training Summer School 2024 Dates: *8 — 12 July 2024* Location: *Technical University of Moldova*, Chișinău, Moldova Coordinating Project: UNIDIVE <https://unidive.lisn.upsaclay.fr/doku.php?id=start> (Universality, Diversity and Idiosyncrasy in Language Technology) Website: https://unidive.lisn.upsaclay.fr/doku.php?id=meetings:other-events:1st_unid… Cost: *Participants selected on the basis of their application will be reimbursed, details are below.* *Apply by:* *May 01, 2024* CALL FOR APPLICATIONS We are happy to announce the 1st edition of UNIDIVE Summer School on Universality, Diversity and Idiosyncrasy in Language Technology. It is dedicated mainly (but not exclusively) to young researchers and investigators. Researchers working on low-resourced languages, dialects and varieties are particularly welcome SUMMER SCHOOL ACTIVITIES - Annotation of Universal Dependencies treebank for a new language - a course by Sylvain Kahane (Université Paris Nanterre, France) and Francis Tyers (Indiana University, USA) - Annotation of multiword expressions in a new language - course by Verginica Mititelu (Romanian Academy) and Voula Giouli (Aristotle University of Thessaloniki and ILSP, ATHENA RC, Greece) - Corpus annotation infrastructure (annotation platforms, format validators, Git etc.) - a course by Daniel Zeman (Charles University, Czechia), Bruno Guillaume (LORIA, France) and Agata Savary (Université Paris-Saclay, France) - A brainstorming hackathon on topics submitted by the trainees - Poster sessions APPLICATIONS AND SUBMISSION GUIDELINES Each applicant should *submit a project* for a construction of a resource related to the topics of the training school (e.g. a new/enhanced UD treebank, a new PARSEME corpus, a resource adding a new annotation layer on top of a UD/PARSEME corpus, etc.). The length of the application should be 2 pages (excluding references). The application should contain: - The title - Applicant’s name and affiliation (including the country) - A list of 3-4 key-words - Description of a resource related to the topics of the training school - Explanation how the participation in the training school will be useful for the project - Open questions related to the project which could be addressed during the brainstorming hackathon - Short statement of the project phase (planning, started, in the process of creation) The projects are to be submitted via the OpenReview <https://openreview.net/group?id=UniDive/2024/Training_School> portal. TRAINEE’S SELECTION CRITERIA We can fund at least 40 trainees, the selection criteria include: - Trainee’s country: trainees only from COST countries[1] <#m_5787468061823227072_m_-5162026155145348429__ftn1> and Near-Neighbour Countries can be funded. See here <https://www.cost.eu/about/members/> and here <https://www.cost.eu/about/strategy/international-collaboration/>. - Age: Young Researchers and Investigators, i.e. under the age of 40, are promoted - Gender and geographical balance (notably between Inclusiveness Target Countries and others COST countries) - Relevance and quality of the project submitted by the trainee - Status of the language on which the trainee intends to work (low-resourced languages, dialects or varieties are promoted) *If you are not selected on the basis of these criteria and you can find other financial sources to cover your travel, accommodation and meals, you are also welcome to participate. * *The authors of the selected projects may optionally present them in a poster session during the Training School. * IMPORTANT DATES Deadline for project submission: May 01, 2024 Notification of acceptance: May 15, 2024 Summer school: July 8-12, 2024 For any inquiry, please contact the organisers at: victoria.bobicev(a)ia.utm.md Looking forward to seeing you in Moldova, Organizing Committee ------------------------------ [1] <#m_5787468061823227072_m_-5162026155145348429__ftnref1> COST members include 3 categories: COST Full Members, COST Cooperating Members (Israel), COST Partner Members (South Africa).

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Job offer: Position as research assistant in the DFG project "ENTAILab - Research Infrastructure and Innovation Laboratory" at Goethe University Frankfurt - Application deadline: 14.05.2024
by Andy Lücking 26 Apr '24

26 Apr '24

***Apologues or cross-postings*** At the Institute of Computer Science (Prof. Dr. Alexander Mehler, TTLab, https://www.texttechnologylab.org/), Department of Computer Science and Mathematics at Goethe University Frankfurt, two PhD positions for Research Assistants (m/f/d) (E 13 TV-G-U, 75% part-time) are available at the next possible date for a period of three years within the project ENTAILab - Research Infrastructure and Innovation Laboratory. The two positions can be divided into one full-time and one 50% position by mutual agreement. The project is part of the Infrastructure Priority Programme New Data Spaces for the Social Sciences (SPP 2431, see https://www.new-data-spaces.de/en-us/), which is funded by the German Research Foundation (DFG). The salary group classification is based on the job characteristics determined by the collective labour agreement in effect for the Goethe University (TV-G-U). The aim of the project is to establish a research-oriented infrastructure for new types of data in survey research. To this end, a method-oriented innovation laboratory for novel methods in survey research is to be set up, which will develop and test methods of machine learning and artificial intelligence in cooperation with the projects of the SPP. The subject of the methods to be developed is multimodal data and therefore not primarily or exclusively linguistic research data. The applicant is expected to contribute to the project and actively participate in the workshops and events of the SPP. We are looking for a highly qualified individual with a strong interest in working in the field of cutting-edge research infrastructures, and in team-oriented development and application of innovative, research-oriented methods in the field of survey research and social sciences. With the SPP New Data Spaces for the Social Sciences and the Text-Technology Lab, in which the position will be embedded, we offer two research-oriented, internationally focused working environments in the fields of computational humanities, multimodal computing, machine learning and artificial intelligence. This includes funding for conference attendance and individual career development. Requirements: • Completed academic university degree (Master's) in a relevant subject with a focus on information science. • Very good English language skills (C1). • Demonstrable experience with databases and methods of machine learning or artificial intelligence. • Extensive programming skills in Java, Python or similar. • Knowledge of virtualization technologies such as Docker, Kubernetes or similar. • An interest in social science issues is desirable. Please send your application with the usual documents (cover letter, CV, copies of certificates) electronically in a summarized PDF document by 14.05.2024 to Prof. Dr. Alexander Mehler: mehler(a)em.uni-frankfurt.de.

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