June 2024 - Kdml - lists.cs.uni-kassel.de

Precall "Bilateral AI" (50 PhDs, 10 Postdocs), fall 2024

by Johannes Fürnkranz

Cluster of Excellence Bilateral Artificial Intelligence Pre-Call for Applications For the recently established Cluster of Excellence CoE Bilateral Artificial Intelligence (BILAI), funded by the Austrian Science Fund (FWF), we are looking for more than 50 PhD students and 10 Post-Doc researchers (m/f/d) to join our team at one of the six leading research institutions across Austria (see below). In BILAI, major Austrian players in Artificial Intelligence (AI) are teaming up to work towards Broad AI. As opposed to Narrow AI, which is characterized by task-specific skills, Broad AI seeks to address a wide array of problems, rather than being limited to a single task or domain. To develop its foundations, BILAI employs a Bilateral AI approach, effectively combining sub-symbolic AI (neural networks and machine learning) with symbolic AI (logic, knowledge representation, and reasoning) in various ways. Harnessing the full potential of both symbolic and sub-symbolic approaches can open new avenues for AI, enhancing its ability to solve novel problems, adapt to diverse environments, improve reasoning skills, and increase efficiency in computation and data use. These key features enable a broad range of applications for Broad AI, from drug development and medicine to planning and scheduling, autonomous traffic management, and recommendation systems. Prioritizing fairness, transparency, and explainability, the development of Broad AI is crucial for addressing ethical concerns and ensuring a positive impact on society. The research team is committed to cross-disciplinary work in order to provide theory and models for future AI and deployment to applications. CoE Research Institutions: Johannes Kepler Universität Linz (JKU Linz) Technische Universität Wien (TU Wien) Alpen-Adria-Universität Klagenfurt (AAU) Institute of Science and Technology Austria (ISTA) Technische Universität Graz (TU Graz) Wirtschaftsuniversität Wien (WU Wien) Board of directors: Sepp Hochreiter (JKU Linz) Agata Ciabattoni (TU Wien) Thomas Eiter (TU Wien) Gerhard Friedrich (AAU) Christoph Lampert (ISTA) Robert Legenstein (TU Graz) Axel Polleres (WU Wien) Martina Seidl (JKU Linz) The call for applications will open on *** September 1,*** 2024. For more information, see http://www.bilateral-ai.net Stay tuned! -- Johannes Fürnkranz Computational Data Analytics Institute for Application Oriented Knowledge Processing (FAW) Johannes Kepler University Linz

3 months, 1 week

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Postdoc position in Psychologically-informed User Modeling

by Marko Tkalcic

TLDR: postdoc position (PhD required), full-time employment (40 hrs/week), duration 2 years (preferred start October 2024), research and teaching, supervisor: Marko Tkalčič, University of Primorska, Koper, Slovenia Research topics: - psychologically-informed user modeling, - psychologically-informed item modeling, - inference of user and item characteristics, - explanations, - recommender systems. Interested candidates can find me at UMAP next week to discuss it. Details: The Department of Information Sciences and Technologies (DIST) at the Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT) of the University of Primorska is seeking a top early-career researcher for a postdoctoral position in the area of psychologically-informed user modeling under the supervision of assoc. prof. dr. Marko Tkalčič. The project will explore how psychologically-informed features can be used to model users, items, infer user characteristics from digital traces, infer item characteristics, provide explanations and recommendations in the music and film domains. The methodologies will include user studies and machine learning. The candidate will work in a great team with Marko Tkalčič as part of the HICUP lab (https://hicup.famnit.upr.si/) in the beautiful Mediterranean city of Koper (the beach is only a 3 min walk from the office). - Full-time employment (40 hrs/week). Full social security. - The position is for two years. - The preferred starting date is October 2024. - The candidate must have (or expect to obtain shortly) a PhD in computer science or in an area relevant to the research topics. - The ideal candidate should posses expertise in the following areas: - recommender systems, - machine learning, - user modeling. - Expertise in one or more of the following areas will be appreciated: - ML explainability, - computational psychology, - computational social science, - media-related knowledge (musicology etc.). - The position includes a small teaching load (1 course/semester, 3-4 hrs/week). - The position comes with funding for travel (conferences, visitors). Application Process: The applications will be assessed on a rolling basis until the position is filled. To apply, send an email to marko.tkalcic(a)famnit.upr.si with the following documentation: - motivation letter, - CV, - list of publications, - research statement, - names and email addresses of two to three references. Link to call: https://markotkalcic.com/postdoc_2024.html -- ---------------------------------------------------------------------- Dr. Marko Tkalcic http://markotkalcic.com Twitter: https://twitter.com/#!/RecSysMare Linkedin: http://www.linkedin.com/in/markotkalcic Google Scholar: http://scholar.google.com/citations?user=JQ2puysAAAAJ ----------------------------------------------------------------------

3 months, 1 week

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[CfP] LWDA-KDML 2024 Deadline Extension to July 14, 2024

by schloer＠informatik.uni-wuerzburg.de

Dear colleagues, we would like to bring your attention to the deadline extension for this year's LWDA KDML workshop taking place in Würzburg from September 23 to September 25. This year, the meeting will be co-located with the KI 2024 conference. The new submission deadline is: July 14, 2024 We invite submissions on all aspects of data mining, knowledge discovery, and machine learning. In addition to original research, we also invite resubmissions of recently published articles related to KDML at major conference venues. Moreover, KDML explicitly invites student submissions. Please find the full Call for Papers here: https://www.informatik.uni-wuerzburg.de/lwda24/kdml/ We are looking forward to receiving your submissions. Best regards, Daniel Schlör and Simon Klüttermann, KDML workshop organizers

3 months, 1 week

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Position for 3 years PhD or PostDoc

by Anni-Yasmin Turhan

Dear all, there is an open position for a PhD student or a PostDoc in the new knowledge representation group at Paderborn University! This is a full position for three years. The KR group is associated to the research area of Data Science at the Computer Science institute of the university and is dedicated to foundational research on logical formalisms and their reasoning problems. Current research topics are reasoning methods in formal ontology languages (Description Logics), in particular, ontology-mediated query answering, learning in description logics, and forms of nonmonotonic reasoning. We offer a friendly and flexible working environment in a dynamic and research-oriented team within an international research network. A successful applicant would have • good background in formal methods, e.g. logic, complexity theory and model theory • a masters degree / PhD in computational logic or related fields • good English speaking and writing skills; speaking German is a plus • experience in implementing complex systems is a plus For further details on the PostDoc position and the application procedure see https://cs.uni-paderborn.de/fileadmin-eim/informatik/fg/kr/Kennziffer6531_-… . The application deadline for the position is July 31st 2024. Should you have questions about the positions or the application procedure, please send an email to turhan<at>uni-paderborn.de . Best regards, Anni-Yasmin Turhan -- -- Prof. Dr. Anni-Yasmin Turhan Knowledge Representation Group University of Paderborn

3 months, 1 week

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[CFP - WSDM 2025]The 18th ACM International Conference on Web Search and Data Mining

by Megha Khosla

The International Conference on Web Search and Data Mining (WSDM) invites submissions for its 2025 edition, to be held from March 10th-14th, 2025, organized at Hannover, Germany. WSDM is a premier forum for presenting and discussing the latest advances in web search and data mining, bringing together researchers and practitioners from academia and industry. Important Dates: =========== Abstract Submission Deadline: [August 7, 2024] Paper Submission Deadline: [August 14, 2024] Notification of Acceptance: [October 23, 2024] Camera-ready Deadline: [December 18, 2024] Conference Dates: [March 10-14, 2025] Topics: =========== Topics of interest include, but are not limited to: Web Search Web Mining and Content Analysis Web of Things, Ubiquitous and Mobile Computing Privacy, Fairness, Interpretability Social Networks Intelligent Assistants Crowdsourcing and Human Computation Emerging and Creative Applications Information Integrity Foundation Models Submission Guidelines: ============== Papers must be formatted according to the ACM SIG proceedings template. Submissions will undergo a rigorous double-blind review process by the Program Committee. Papers should be submitted electronically through the conference submission system by the deadline specified above. Publication: ======= Accepted papers will be published in the conference proceedings, available through the ACM Digital Library. Website: ====== For the latest updates and information, please visit the conference website: https://www.wsdm-conference.org/2025/#calls <https://www.wsdm-conference.org/2025/#calls> Join us at WSDM 2025 to explore the frontier of web search and data mining research and innovation!

3 months, 2 weeks

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Stellen im BMBF-Projekt „Ethische Implikationen hybrider Teams aus Mensch und KI-System (Ethyde)“ am bidt München

by Ute Schmid

Für das BMBF-Projekt „Ethische Implikationen hybrider Teams aus Mensch und KI-System (Ethyde)“ sind zwei Stellen am Bayerischen Forschungsinstitut für Digitale Transformation (bidt) in München zu besetzen. Das Projekt wird von Ute Schmid (Lehrstuhl Kognitive Systeme an der Universität Bamberg), Mitglied im Direktorium des bidt, geleitet. Wissenschaftliche:r Mitarbeiter:in (Postdoc) (m/w/d) im Bereich Künstliche Intelligenz <https://bidt.jobs.personio.de/job/1601658> https://bidt.jobs.personio.de/job/1601658?display=de Wissenschaftliche:r Mitarbeiter:in (Predoc) (m/w/d) im Bereich Kognitionspsychologie in Teilzeit (50%) <https://bidt.jobs.personio.de/job/1601786> https://bidt.jobs.personio.de/job/1601786?display=de -- Prof. Dr. Ute Schmid Cognitive Systems University of Bamberg, An der Weberei 5 (room WE5/05.43) phone ++49-951-863-2860, -2861 (secr.), www.uni-bamberg.de/en/cogsys/schmid www.uni-bamberg.de/bacai www.bidt.digital www.iis.fraunhofer.de/explainable-AI

3 months, 2 weeks

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[CfP] [CoKA] : --- 2nd Call --- "Conceptual Knowledge Acquisition: Challenges, Opportunities, and Use Cases" workshop at CONCEPTS 2024

by Tom Hanika

***CoKA: --- 2nd Call for Contributions*** ================================================================ Conceptual Knowledge Acquisition: Challenges, Opportunities, and Use Cases Workshop at the 1st International Joint Conference on Conceptual Knowledge Structures (CONCEPTS 2024) September 9–13 2024, Cádiz, Spain Workshop Website: https://www.kde.cs.uni-kassel.de/coka/ Conference website: https://concepts2024.uca.es ================================================================ Formal concept analysis (FCA) can help make sense of data and the underlying domain --- provided the data is not too big, not too noisy, representative of the domain, and if there is data in the first place. What if you don’t have such data readily available but are prepared to invest in collecting it and have access to domain experts or other reliable queryable sources of information? Conceptual exploration comes to the rescue! Conceptual exploration is a family of knowledge-acquisition techniques within FCA. The goal is to build a complete implicational theory of a domain (with respect to a fixed language) by posing queries to a domain expert. When properly implemented, it is a great tool that can help organize the process of scientific discovery. Unfortunately, proper implementations are scarce and success stories of using conceptual exploration are somewhat rare and limited in scope. With this workshop, we intend to analyze the situation and, maybe, find a solution. If - you succeeded in acquiring new knowledge about or building a satisfying conceptual representation of some domain with conceptual exploration before; - you attempted conceptual exploration in application to your problem but failed miserably; - you want to use conceptual exploration to analyze some domain, but you don’t know where and how to start; - you are aware of alternatives to conceptual exploration; then come to the workshop to share your experiences, insights, ideas, and concerns with us! ================== Keywords and Topics ================== Knowledge Acquisition and Capture Conceptual Exploration Design Patterns and Paradigmatic Examples successful use cases and real-world applications challenges and lessons learned application principles missing theoretical foundations missing technical infrastructure integration with other theories and technologies ========================= Duration, Format, and Dates ========================= We invite contributions in the form of an extended abstract of up to two pages. In addition, supplementary material, such as data sets, detailed descriptions, or visualizations, may be submitted. The workshop is planned for half a day within the conference dates and at the same venue. It will consist of several short presentations each followed by a plenary discussion. Please send your contributions until *July 10, 2024* to tom.hanika(a)uni-hildesheim.de. If you are not sure whether your contribution matches the topics or the format of the workshop, you are welcome to contact the organizers prior to submitting the abstract. An acceptance notification will be sent within two weeks upon receiving the submission. =================== Workshop Organizers =================== - Tom Hanika, University of Hildesheim - Sergei Obiedkov, TU Dresden - Bernhard Ganter, Ernst-Schröder-Zentrum, Darmstadt -- Dr. Tom Hanika Universität Kassel Tel.: +49 (0) 561 804 6252 https://www.kde.cs.uni-kassel.de/hanika ---------------------------------------------------------------------

3 months, 2 weeks

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Stellenangebot in Berlin: Promotionsstelle neuro-symbolische künstliche Intelligenz

by Robert Jäschke

Die Arbeitsgruppe Information Processing and Analytics der Humboldt-Universität zu Berlin befasst sich mit der Extraktion von Wissen aus großen Datenmengen und erforscht dabei Technologien und Verfahren aus den Bereichen Data Mining & Machine Learning, Linked Data, Information Extraction und Natural Language Processing. Zur Verstärkung unseres Schwerpunktes Neuro-symbolische Künstliche Intelligenz ist ab sofort eine Promotionsstelle zu besetzen. (Wiss. Mitarbeiter*in befristet für vorauss. 4 Jahre - E 13 TV-L HU) Mögliche Anwendungsfelder sind die - Erkennung und Extraktion rhetorischer Stilmittel in großen Textkorpora, - Extraktion und Verlinkung bibliographischer Metadaten in geisteswissenschaftlichen Publikationen, - temporale Analyse von (archivierten) Web-Inhalten. Aufgabengebiete: - wissenschaftliche Dienstleistungen in Forschung und Lehre - Aufgaben zur eigenen wissenschaftlichen Qualifikation (Promotion) - wissenschaftliche Betreuung der Datensammlungen der Arbeitsgruppe sowie der zugehörigen Analyseumgebung - Aufbau eines Dienstes zur Nutzung und Erforschung von großen Sprachmodellen (LLMs), insbesondere für die Digital Humanities - Mitarbeit am Social-Bookmarking-System BibSonomy Ihr Profil: Erforderlich sind: - guter Universitätsabschluss in Informatik oder verwandten Fächern (Abschlussarbeit muss zumindestet eingereicht sein) - sehr gute Programmierkenntnisse und Erfahrung im Umgang mit modernen Softwareentwicklungs-Werkzeugen - gute Kenntnisse in mindestens einem der folgenden Bereiche: Data Mining/Machine Learning, Web Crawling, Informationsextraktion, Natural Language Processing, Named Entity Recognition and Linking - sehr gute Deutsch- und gute Englischkenntnisse in Wort und Schrift Erwünscht sind: - Interesse an teamorientierter Forschungsarbeit auf internationalem Niveau in einem interdisziplinären Team - Interesse an der Verarbeitung großer Datenmengen und der Betreuung der entsprechenden Infrastruktur - sehr gute Organisationsfähigkeit, Belastbarkeit und soziale Kompetenz - sehr gute Kommunikationsfähigkeit Die Bereitschaft zu gelegentlichen Dienstreisen aus Anlass von Projekttreffen oder Tagungen wird erwartet. Unser Angebot: - eine abwechslungsreiche Tätigkeit in einem dynamischen und spannenden Forschungsumfeld, in dem Teamarbeit, Transparenz, offene Innovationsprozesse und ständige Weiterbildung unverzichtbar sind - leistungsorientiertes und forschungsstarkes Team - die Altersvorsorge für den öffentlichen Dienst (VBL) - flexible Arbeitszeiten und Homeoffice-Regelungen bzw. ein Arbeitsplatz in Berlin Mitte - Austausch und Kooperation mit den Mitarbeiter*innen und Doktorand*innen des Instituts für Bibliotheks- und Informationswissenschaft - Chancengleichheit und Vereinbarkeit von Beruf und Familie - die Möglichkeit, ausgiebig Erfahrung im Umgang mit großen Datenmengen sowie der geeigneten Infrastruktur (Cluster-System) und aktuellen Technologien (z.B. Apache Spark) zu sammeln Bewerbungen (mit Anschreiben, Lebenslauf und relevanten Zeugnissen sowie einer informativen Kurzzusammenfassung der letzten Abschlussarbeit (max. eine Seite) richten Sie bitte bis zum *05.07.2024* unter Angabe der Kennziffer *AN/116/24* an die Humboldt-Universität zu Berlin, Philosophische Fakultät, Institut für Bibliotheks- und Informationswissenschaften, Prof. Robert Jäschke, Unter den Linden 6, 10099 Berlin oder bevorzugt per E-Mail in einer PDF-Datei an robert.jaeschke(a)hu-berlin.de. Auf die Vorlage von Lichtbildern/Bewerbungsfotos verzichten wir ausdrücklich und bitten daher, hiervon abzusehen. Bei Fragen wenden Sie sich gern an Prof. Dr. Robert Jäschke (robert.jaeschke@hu- berlin.de). Zur Sicherung der Gleichstellung sind Bewerbungen qualifizierter Frauen besonders willkommen. Schwerbehinderte Menschen werden bei gleicher Eignung bevorzugt. Bewerbungen von Menschen mit Migrationsgeschichte sind ausdrücklich erwünscht. Da wir Ihre Unterlagen nicht zurücksenden, bitten wir Sie, Ihrer Bewerbung nur Kopien beizulegen. Datenschutzrechtliche Hinweise zur Verarbeitung Ihrer personenbezogenen Daten im Rahmen des Ausschreibungs- und Auswahlverfahrens finden Sie auf der Homepage der Humboldt-Universität zu Berlin: https://hu.berlin/DSGVO. -- Prof. Dr. Robert Jäschke Humboldt-Universität zu Berlin < https://hu.berlin/RJ >>>>>>>>>>><<<<<<<<<<< +49 (0)30 2093-70960 > < https://weltliteratur.net/ >>>>><<<<< https://dev.bibsonomy.org/ >

4 months

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Kdml June 2024