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CfP - LWDA 2023 - Deadline July 20

by Helge Spieker

*Call for Papers LWDA 2023* (KDML CfP below) The annual conference LWDA <http://www.lwda2023.de/>, which expands to „Lernen, Wissen, Daten, Analysen“ („Learning, Knowledge, Data, Analytics“), covers current research in areas such as knowledge discovery, machine learning & data mining, knowledge management, database management & information systems, information retrieval. The conference will be held at the Philipps University of Marburg from *9 to 11 October 2023* and welcomes submissions of innovative research from both industry and academia. The LWDA conference brings together the various special interest groups of the Gesellschaft für Informatik (German Computer Science Society) in this area: - FG Datenbanksysteme – Data Engineering for Data Science <https://www.uni-marburg.de/de/fb02/professuren/bwl/digiprozess/lwda2023-2/c…> - FG Knowledge Discovery und Machine Learning <https://www.uni-marburg.de/de/fb02/professuren/bwl/digiprozess/lwda2023-2/c…> - FG Business Intelligence und Analytics <https://www.uni-marburg.de/de/fb02/professuren/bwl/digiprozess/lwda2023-2/c…> - FG Knowledge Management <https://www.uni-marburg.de/de/fb02/professuren/bwl/digiprozess/lwda2023-2/c…> - FG Information Retrieval <https://www.uni-marburg.de/de/fb02/professuren/bwl/digiprozess/lwda2023-2/c…> The program includes joint research sessions and keynotes, as well as workshops organised by each special interest group. We're looking forward to see you at the conference and are looking forward to your submission! *Call for Papers KDML @ LWDA 2023* 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 at major conference venues related to KDML. Moreover, KDML explicitly invites student submissions. Topics of interest include but are not limited to: 1. Foundations, algorithms, models, and theory of machine learning and data mining 2. Supervised, semi-supervised, and unsupervised learning 3. Machine learning on networks and graphs 4. Deep learning and representation learning 5. Rule-based learning and pattern mining 6. Reinforcement learning 7. Fairness, transparency and formal guarantees in machine learning 8. Explainability and Interpretability in machine learning and knowledge discovery 9. Trustworthiness in machine learning and knowledge discovery 10. Temporal, spatial & spatio-temporal data analytics 11. Online learning and machine learning in data streams 12. Text mining, mining unstructured and semi-structured data 13. Parallel and distributed data analytics 14. Interactive and visual analytics 15. Applications of data mining and machine learning in all domains including natural-, life-, and social sciences, health, financial, environment, engineering, and humanities 16. Open source frameworks and tools for data mining and machine learning *Submission deadline:* July 20, 2023 *Notification of acceptance:* August 20, 2023 *Camera-ready copy:* September 14, 2023 *Workshop:* October 9 – 11, 2023 *Full Call for Papers: * https://www.uni-marburg.de/de/fb02/professuren/bwl/digiprozess/lwda2023-2/c… Workshop Organisation Felix Stamm, Rheinisch-Westfälische Technische Hochschule Aachen Dr. Helge Spieker, Simula Research Laboratory, Oslo, Norway Best regards, Helge Spieker -- Helge Spieker Research Scientist Simula Research Laboratory Oslo, Norway

2 years

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Three Open Rank Professorships in the field of Machine Learning and Artificial Intelligence

by Prof. Dr. Emmanuel Müller

Dear colleagues, here's your opportunity to shape the future of Machine Learning and Artificial Intelligence as part of our research institute. The Lamarr Institute [1] and TU Dortmund University [2] are looking for three open rank professorship positions to be filled as early as possible: THREE PROFESSORSHIPS IN THE FIELD OF MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE (Open Rank: W3 tenured or W2 with W3 tenure track) at the Department of Computer Science, TU Dortmund University https://service.tu-dortmund.de/documents/18/2120803/Job_Advertisements_Prof… [3] If you are interested, please drop us a message. We are seeking an outstanding scientist who holds an excellent PhD in Computer Science or related disciplines, has experience in applying for third-party funds and has published in relevant and highly ranked international venues with peer review. In particular, we welcome applications of candidates who have conducted excellent research in one or more of the following areas: * Foundations of Artificial Intelligence * Theory of Deep Learning * Neuro-Symbolic Artificial Intelligence * Explainable Artificial Intelligence * Causality * Machine Learning and Logic * Fairness and Transparency of Machine Learning * Ressource Aware Machine Learning * Reinforcement Learning * Large-Scale Generative Models * Simulation-Based Machine Learning * Large Scale Optimization * Federated Learning * Future Applications of Machine Learning IF YOU ARE INTERESTED IN THE POSITION, PLEASE SEND YOUR APPLICATION VIA E-MAIL BY AUGUST 2ND TO: BEWERBUNG(a)CS.TU-DORTMUND.DE The Lamarr Institute, as a leading international center for Machine Learning, focuses on the value-based research and development of high-performance, trustworthy, and resource-efficient applications of Machine Learning and Artificial Intelligence (AI). It establishes internationally competitive research that sustainably strengthens Germany and Europe as leading locations for research, education, and technology transfer in AI. Along the central research paradigm of „Triangular AI" (AI3), Lamarr scientists are laying the foundations for the next generation of Artificial Intelligence, which uses data, knowledge and context of intelligent systems on an equal footing. The Department of Computer Science at TU Dortmund University is one of the largest in Germany and has particular strengths in research. Among similar institutions, it is distinguished by a combination of fundamental research on formal methods with the development of practical applications. Research focuses on Algorithmics, Data Science, Cyber-Physical Systems and Software and Service Engineering. Bests, Emmanuel Müller -- Prof. Dr. Emmanuel Müller emmanuel.mueller(a)cs.tu-dortmund.de Professor of Computer Science Technical University of Dortmund Chair of Data Science and Data Engineering https://ls9-www.cs.tu-dortmund.de/ [4] LAMARR Institute for Machine Learning and Artificial Intelligence https://lamarr-institute.org/ [1] Director of Research Center Trustworthy Data Science and Security https://rc-trust.ai/ [5] Links: ------ [1] https://lamarr-institute.org/ [2] https://www.tu-dortmund.de/ [3] https://service.tu-dortmund.de/documents/18/2120803/Job_Advertisements_Prof… [4] https://ls9-www.cs.tu-dortmund.de/ [5] https://rc-trust.ai/

2 years

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Postdoc Position - AI & Data Science - UOS

by Martin Atzmüller

Dear colleagues, we offer a position for a PostDoc with research related to explainable/interpretable learning, semantic methods, and/or modeling complex relational/multi-modal data. Detailed information about the position and how to apply is available here: https://www.uni-osnabrueck.de/universitaet/stellenangebote/stellenangebote-… The deadline for applications is June 30, 2023. Please feel free to contact me to discuss further details. Best regards, Martin Atzmueller -- Prof. Dr. Martin Atzmueller https://martin.atzmueller.net | https://sis.cs.uos.de ROSEN-Group-Endowed Chair of Semantic Information Systems Institute of Computer Science, Osnabrück University (UOS) & German Research Center for AI (DFKI) & Founding Spokesperson of the Joint Lab AI & Data Science | https://jl-ki-ds.uos.de

2 years

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Research Associate/PhD (m/f/d) position at the Division of Psychological Methods and Statistics, Oldenburg, Germany

by Jörge Minula

Dear Members, I would like to bring to your attention a PhD position available at the Division of Psychological Methods and Statistics, University of Oldenburg, Germany. For more information about the position and how to apply, please refer to the detailed description provided in the email below. Best regards, Jörge Minula ------------------------------ School VI of Medicine and Health Sciences comprises the fields of human medicine, medical physics and acoustics, neurosciences, psychology and health services research. Together with the four regional hospitals, School VI forms the University Medicine Oldenburg. Furthermore, there is close cooperation with the University Medicine of the University of Groningen. In the organization unit for Psychological Methods and Statistics of the Department of Psychology there is a vacancy for a *Research Associate/PhD (m/f/d)* (E13 TV-L, 100%) <https://lohntastik.de/od-rechner/tv-gehaltsrechner/TV-L/E-13/1> *starting October 2023 *for a limited period of 3 years. There is the possibility of personal scientific qualification (doctorate/post-doctoral thesis). The position is suitable for part-time work. At the Division of Psychological Methods and Statistics we develop and apply multivariate statistical modeling techniques and technologically advanced instrumentation for research in behavioral and health sciences. By means of these tools, applicable to modeling neurometric (EEG, DTI, fMRI, fNIRS) and psychometric data, collected within and outside the lab, we aim to understand individual differences and intraindividual fluctuations in typical and disordered sensory, cognitive and emotional processing and their behavioral outcomes across the lifespan – from neonatal age to late adulthood. The methodological and substantive topics we work at are diverse, but they inspire each other. We are committed to implementing Open Science techniques to foster reproducibility in our research and beyond. The position advertised here will work on structural and functional neuroimaging with the aim of developing advanced methods (complex dynamic networks) for measuring neuromarkers of cognitive sequelae after preterm birth. Tasks include: - Collaboration in teaching (4 LVS) - Research with close links to the research priorities of the working group and the above elaborated topic - Writing scientific papers - Presenting results at scientific conferences - Engaging with Open Science practices and contributing to the Department's Open Science Interest Group <https://uol.de/psychologie/open-science/osig>. Recruitment requirements: - Completed scientific university studies (Diploma / Master) in the field of Psychology, Cognitive Neuroscience and related disciplines - Neuroimaging data analysis experience - Robust and broad knowledge of multivariate statistics, including Structural Equation Modeling - Knowledge of standard machine learning tools - Very good programming skills on R and Python Advantageous are: - Knowledge in clinical, personality, social and / or cognitive neuroscience - Very good scientific presentation skills - Prior experience with Open Science practices We offer: - A friendly and diverse work environment - A close mentoring toward an academic career - Payment in accordance with collective bargaining law (special annual payment, company pension scheme, asset-related benefits) incl. 30 days annual leave - Support and guidance during your induction phase - A family-friendly environment with flexible working hours (flexitime) and the possibility of pro-rata mobile work - Benefits from the university's health promotion programme - An extensive free further education programme as well as our own scientific promotion of young academics (https://uol.de/medizin/nachwuchs ) The University of Oldenburg aims to increase the proportion of women in the academic field. Therefore, women are strongly encouraged to apply. According to § 21 para. 3 NHG, female applicants should be given preferential consideration if their qualifications are equivalent. Applicants with disabilities are given preference in the event of equal suitability. For further information, please contact Prof. Dr. Andrea Hildebrandt ( https://uol.de/psychologie/statistik/prof-dr-andrea-hildebrandt). How to apply: Follow the description at https://uol.de/stellen?stelle=69636

2 years

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Call for Participation: 17th Intl. Conf. on Formal Concept Analysis (ICFCA 2023)

by Gerd Stumme

================================================================================ ICFCA 2023 17th International Conference on Formal Concept Analysis July 17-21, 2023, Kassel, Germany Web: https://www.kde.cs.uni-kassel.de/icfca2023/ ================================================================================ REGISTRATION: https://www.kde.cs.uni-kassel.de/icfca2023/register.html The EARLY-BIRD registration is closing soon: June 15 (AoE) PROGRAM: https://www.kde.cs.uni-kassel.de/icfca2023/program.html ================================================================================ ICFCA will feature exiting INVITED TALKS: * KEYNOTES - Oliver Deussen (University of Konstanz, Germany): How to Visualize Sets and Set Relations - Reinhard Diestel (University of Hamburg, Germany): Tangles: from Wittgenstein to graph minors and back - Jan Konečný (Palacký University Olomouc, Czech Republic): Formal Concept Analysis in Boolean Matrix Factorization: Algorithms and Extensions to Ordinal and Fuzzy-Valued Data - Manuel Ojeda Aciego (University of Málaga, Spain): On the φ-degree of inclusion - Alessandra Palmigiano (Vrije Universiteit Amsterdam, Netherlands): Logical foundations of categorization theory - William T. Trotter (Georgia Tech Institute, USA): Modern Concepts of Dimension for Partially Ordered Sets * LATEBREAKING RESULT TALK - Christian Jäkel (TU Dresden, Germany): Breaking the Barrier: A Computation of the Ninth Dedekind Number The ICFCA Organizing Committee is looking forward to meeting You in Kassel! Gerd Stumme (General Chair) Dominik Dürrschnabel (PC Co-Chair) Domingo López Rodríguez (PC Co-Chair)

2 years

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Promotionsstelle Data Science für hierarchische Daten an der Universität Kassel

by Gerd Stumme

Das Fachgebiet Wissensverarbeitung der Universität Kassel schreibt eine Stelle für eine:n Wissenschaftliche:n Mitarbeiter:in (m/w/d, TV-H E13, 100 %) im Rahmen des Forschungsprojekts "Towards Ordinal Data Science" unter Leitung von Prof. Dr. Gerd Stumme aus. Das Fachgebiet forscht an der Schnittstelle von Data Science und Künstlicher Intelligenz. Aufgabe der Promotionsstelle ist die Erforschung von Data-Science-Methoden für hierarchische Daten. Das Fachgebiet ist Mitglied im Wissenschaftlichen Zentrum für Informationstechnik-Gestaltung (ITeG) und im Hessian Center for Artificial Intelligence (hessian.AI). Weitere Informationen finden Sie unter https://www.kde.cs.uni-kassel.de/ . Wir suchen eine:n hochmotivierte:n Doktorand:in, der/die eine mathematisch orientierte Arbeitsweise mitbringt und bereit zu interdisziplinärer Zusammenarbeit ist. Wir bieten Ihnen ein teamorientiertes Forschungsumfeld, die Gelegenheit, erste Lehrerfahrung zu sammeln, sowie die Möglichkeit, ihre Ergebnisse international zu publizieren und auf Konferenzen vorzustellen. Das Anstreben einer Promotion ist möglich und erwünscht. Wir erwarten einen überdurchschnittlichen Universitätsabschluss in Informatik, Mathematik, Physik oder einem verwandten Gebiet, gute Kenntnisse in Programmierung und diskreten Strukturen, eine hohe Eigenmotivation sowie fließende Englischkenntnisse in Wort und Schrift. Bei inhaltlichen Fragen zur Stelle wenden Sie sich gern an Herrn Prof. Dr. Gerd Stumme (stumme(a)cs.uni-kassel.de). Die Universität Kassel ist eine Universität, an der Offenheit, Initiative, fächerübergreifendes und unkonventionelles Denken gewünscht und gefördert werden. Kassel ist die zweitgrünste Stadt Deutschlands und überzeugt mit Lage und Potenzial. Hier ist es grün, aber nicht langweilig. Hier ist es urban, aber nicht überlaufen --> https://www.uni-kassel.de/go/darum-kassel Die Stelle ist befristet auf zunächst drei Jahre und zum frühestmöglichen Termin zu besetzen. Das Gehalt beträgt mindestens 53.000 € pro Jahr. Ihre Bewerbung können Sie bis zum 22.3.2023 im Bewerbungsportal hochladen, wo Sie auch den vollständigen Ausschreibungstext finden: https://www.uni-kassel.de/go/tods-ausschreibung -- Prof. Dr. Gerd Stumme, Hertie Chair of Knowledge & Data Engineering & Research Center for Information System Design (ITeG) & International Center for Higher Education Research (INCHER), University of Kassel & Research Center L3S & The Hessian Center for Artificial Intelligence (hessian.AI) http://www.kde.cs.uni-kassel.de, Tel. +49 561/804-6251

2 years

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Ausschreibung W3-Professur "Wissensverarbeitung in hybriden KI-Systemen" an der Universität Osnabrück (bis: 31.05.2023)

by Martin Atzmüller

Liebe Kolleginnen und Kollegen, bitte weisen Sie geeignete Kandidat:innen auf die Ausschreibung W3-Professur "Wissensverarbeitung in hybriden KI-Systemen" an der Universität Osnabrück hin - siehe: https://www.uni-osnabrueck.de/universitaet/stellenangebote/stellenangebote-… Bewerbungsschluss ist der 31.05.2023. Beste Grüße Martin Atzmüller -- Prof. Dr. Martin Atzmueller https://martin.atzmueller.net | https://sis.cs.uos.de ROSEN-Group-Endowed Chair of Semantic Information Systems Institute of Computer Science, Osnabrück University (UOS) & German Research Center for AI (DFKI) & Founding Spokesperson of the Joint Lab AI & Data Science | https://jl-ki-ds.uos.de

2 years, 1 month

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Call for Participation: ACM/IEEE JCDL 2023, June 26 - 30, 2023, Santa Fe

by Robert Jäschke

*ACM/IEEE JCDL 2023* – June 26 - 30, 2023, Santa Fe, New Mexico https://2023.jcdl.org/ *Rethinking Digital Records*: Exploring new perspectives, challenges, and opportunities for libraries, archives, museums, and galleries The annual ACM/IEEE Joint Conference on Digital Libraries (JCDL) is the primary international event for the inter- and multi-disciplinary community of academics and practitioners in digital libraries coming from computer, information and social sciences, and other related disciplines. JCDL encompasses the many meanings of the term digital libraries, including notions of managing, operating, developing, curating, evaluating, or utilizing collections of data/information/knowledge in various domains. *Participation* JCDL 2023 will take place at the Hilton Santa Fe Historic Plaza, located at: 100 Sandoval St, Santa Fe, New Mexico, 87501, USA. In-person attendance is highly encouraged and all speakers will be on-site. Online attendance is possible, too. For registration, visit https://2023.jcdl.org/registration/. The early-bird deadline is May 30, 2023. There are various discounts for ACM/IEEE members and students. *Programme* Keynote Speakers: - Oksana Bruy (president of the Ukrainian Library Association) - Sarah Lamdan (professor at CUNY School of Law and Author of the book “Data Cartels The Companies That Control and Monopolize Our Information”) - Jessica Polka (executive Director of ASAPbio – Accelerating Science and Publication in biology) Paper Sessions on: - Digital Libraries - Scientometrics - Web Archiving - Information Retrieval - Knowledge Graphs and Knowledge Organization - Digital Humanities and Teaching - AI / ML / Entity Extraction Workshops: - Innovation Measurement for Scientific Communication (IMSC) in the Era of Big Data - Joint Workshop of the 4th Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE2023) and the 3rd AI + Informetrics (AII2023) - 2nd International Workshop on Digital Language Archives - Persistent Identifiers & US Federal Agency Policies - FAIR Data for Large Research Facilities - Web Archiving and Digital Libraries (WADL) 2023 Tutorials: - The Solid Protocol and Its Potential for Open Science - Up and running with ARK persistable identifiers - From Digital Records to Digital Cultural Landscapes: Beyond Digital Library boundaries with DSpace Doctoral Consortium *Organization* - General Chair: Martin Klein (Los Alamos National Laboratory) - Program Chairs: Anat Ben-David (Open University of Israel), Robert Jäschke (Humboldt-Universität zu Berlin), Mat Kelly (Drexel University) - Sponsorship Chair: Anastasia Zhukova (University of Göttingen) - Treasurer: Caroline Trujillo (Los Alamos National Laboratory) - Publicity Chairs: Shawn M. Jones (Los Alamos National Laboratory), Alex Shocklee (Los Alamos National Laboratory) - Proceedings Chair: Sarah Potvin (Texas A&M University) - Volunteer Chair: Brian Cain (Los Alamos National Laboratory) - Workshop/Tutorial Chairs: Mark Phillips (University of North Texas), Laura Wrubel (Stanford University Libraries) - Panel Chairs: Jodi Schneider (University of Illinois Urbana-Champaign), Anne Lauscher (University of Hamburg) - Posters and Demos Chairs: Vicky Rampin (New York University), Norman Meuschke (University of Göttingen) - Doctoral Consortium Chairs: Dana McKay (RMIT University), George Buchanan (University of Melbourne), Cathy Marshall (Texas A&M University) - Student Support Co-Chairs: Jian Wu (Old Dominion University), Sampath Jayarathna (Old Dominion University) *Contact* For any questions about the program you may contact the program chairs by email to jcdl2023(a)easychair.org. -- Prof. Dr. Robert Jäschke Humboldt-Universität zu Berlin & L3S Research Center Hannover < https://amor.cms.hu-berlin.de/~jaeschkr/ >< +49 (0)30 2093-70960 > < https://weltliteratur.net/ >>>>><<<<< https://dev.bibsonomy.org/ >

2 years, 1 month

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Professorship for Human-AI Interaction

by Prof. Dr. Emmanuel Müller

Dear colleagues, here's your opportunity to shape the future of Trustworthy Artificial Intelligence as part of our interdisciplinary research team. The Research Center Trustworthy Data Science and Security [1] is looking for an open rank professorship position to be filled as early as possible: PROFESSORSHIP FOR HUMAN-AI INTERACTION (Open Rank: W3 tenured or W2 with W3 tenure track) at the Department of Computer Science, TU Dortmund University https://static.rc-trust.ai/Full_Professorship_W3_Human-AI_Interaction.pdf [2] If you are interested, please drop us a message. We are seeking an outstanding scientist who holds an excellent PhD in Computer Science or related disciplines, has experience in applying for third-party funds and has published in relevant and highly-ranked international venues with peer review. In particular, we welcome applications of candidates who have conducted excellent research in one or more of the following areas: * Human-AI collaboration * User control of machine learning * Auditing intelligent systems * Design of interactive natural language systems * AI-assisted software engineering * User-centric voice and text assistants * Transparent and explainable artificial intelligence * AI-aided data exploration and visualization * Reinforcement learning from human feedback * Personalization, recommendation and adaptation of algorithms * Human-Computer interaction for intelligent systems * Generative AI and content co-creation * Hybrid intelligence If you are interested in the position, please send your application via e-mail by June 21st to: bewerbung(a)cs.tu-dortmund.de Bests, Emmanuel Müller -- Prof. Dr. Emmanuel Müller emmanuel.mueller(a)cs.tu-dortmund.de Professor of Computer Science Technical University of Dortmund Chair of Data Science and Data Engineering http://ls9-www.cs.tu-dortmund.de/ [3] Founding Director Research Center Trustworthy Data Science and Security University Alliance Ruhr https://rc-trust.ai/ [1] Links: ------ [1] https://rc-trust.ai/ [2] https://static.rc-trust.ai/Full_Professorship_W3_Human-AI_Interaction.pdf [3] http://ls9-www.cs.tu-dortmund.de/

2 years, 1 month

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6 PostDoc positions in Trustworthy, Reliable, and Safe Machine Learning

by Prof. Dr. Emmanuel Müller

Dear colleagues, we have launched our research incubator with currently 6 open PostDoc positions as part of the interdisciplinary Research Center Trustworthy Data Science and Security https://rc-trust.ai, between the Ruhr University Bochum, TU Dortmund University, and the University of Duisburg-Essen * 6 PostDoc positions (100%, E 14 TV-L) https://static.rc-trust.ai/6_Full_PostDoc_Positions_Trustworthy_Data_Scienc… We aim at interdisciplinary research in the listed topics and beyond. With the increasing number of new professors this research incubator will grow as well in topics and size. Hence, we encourage you to apply for related topics that are not yet listed. In addition our first young investigator group on “Trustworthy Machine Learning” has been released, in which we aim for high profile candidates. Beyond the interdisciplinary and international working environment we offer the opportunity to create your own research group with internal and external funding. * Young Investigator Group (100%, E 14 TV-L) https://rc-trust.ai/postdocs_and_young-investigator-groups-RC-Trust.pdf These positions will complement our interdisciplinary graduate program with currently 9 open PhD positions that will be open for collaborations also with the new PostDocs. * 9 PhD positions (100%, E 13 TV-L) https://rc-trust.ai/Open-PhD-Positions-RC-Trust.pdf If you are interested (application deadline is June 2nd) or you may want to share the open positions to your network! Applications are possible via e-Mail: open-positions(a)rc-trust.ai Bests, Emmanuel Müller -- Prof. Dr. Emmanuel Müller emmanuel.mueller(a)cs.tu-dortmund.de Professor of Computer Science Technical University of Dortmund Chair of Data Science and Data Engineering http://ls9-www.cs.tu-dortmund.de/ Founding Director Research Center Trustworthy Data Science and Security University Alliance Ruhr https://rc-trust.ai/

2 years, 1 month

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