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Staff Scientist position at NLM
by ddemner＠gmail.com 19 Sep '22

19 Sep '22

*STAFF SCIENTIST 1 IN BIOMEDICAL NATURAL LANGUAGE PROCESSING* NATIONAL LIBRARY OF MEDICINE, BETHESDA, MARYLAND *POSITION INFORMATION: * The National Library of Medicine (NLM), Lister Hill National Center for Biomedical Communication (LHNCBC) is recruiting for a Staff Scientist 1. The position is in the Computational Health Research Branch (CHRB), which is a part of the Intramural Research Program (IRP). NLM is one of 27 Institutes at the National Institutes of Health (NIH), part of the Department of Health and Human Services (DHHS). NLM IRP is looking for an outstanding candidate with extensive experience in biomedical natural language processing (NLP) with commitment to the biomedical informatics research in areas of fostering and applying discoveries. The responsibilities of this position will include the following activities: · conducting research in the general area of linking electronic medical data (focusing on NLP of narrative documentation) with biological/genomic data; · advancing text mining research, semantic parsing, and machine learning methods; · developing NLP methods for precision medicine; · providing consultation related to informatics applications for clinical decision support; · establishing collaborations with external entities and institutions; and, · working with and mentoring students and post-doctoral fellows. *POSITION REQUIRMENTS: * The ideal candidate may or may not be a United States citizen and must have a doctoral degree. We are looking for an individual with: · a Ph.D. or equivalent in computer science, related disciplines biomedical, or clinical informatics; · experience and a track record in natural language processing research applied to biomedicine documented by peer-reviewed publications; · demonstrated ability to work closely and productively with other research teams; and, · demonstrated ability to initiate and successfully conduct research. *FOREIGN EDUCATION:* Applicants who have completed part or all their education outside of the U.S. must have their foreign education evaluated by an accredited organization to ensure that the foreign education is equivalent to education received in accredited educational institutions in the United States. We will only accept the completed foreign education evaluation. For more information on foreign education verification, visit the National Association of Credential Evaluation Services (NACES) website <https://www.naces.org/>. Verification must be received prior to the effective date of the appointment. Employees, contractors, trainees, and volunteers providing healthcare or services in support of healthcare (Healthcare Workforce) may be required to receive a COVID-19 vaccine because they are expected to perform duties that put them in contact or potential contact with patients. We may request COVID-19 vaccination, and other vaccination documentation from Healthcare Workforce personnel at any point during the onboarding process or at any time during your employment with NIH. For more information on this requirement, visit the Safer Federal Workforce <https://www.saferfederalworkforce.gov/faq/vaccinations/> page on vaccines. If you need a COVID-19 vaccine, please visit Vaccines.gov <https://www.vaccines.gov/>. *SALARY/BENEFITS:* This non-competitive appointment in the excepted service is like a federal full-time position. Salary will be commensurate with experience and qualifications. A full package of benefits <https://www.opm.gov/healthcare-insurance/healthcare/enrollment/new-federal-…> is available. *HOW TO APPLY: * Interested individuals should send a copy of their CV with the names of three references along with a cover letter detailing research interests and evidence of engagement in multi-disciplinary collaborative research to maria.lugo(a)nih.gov. Please include the announcement number, NLM2452-2022, in the cover letter. Do not include your birth date, social security number (SSN), or personal photograph on application materials. Review of applications will begin on September 29, 2022. Applications will be accepted until the position is filled. *COMMITMENT TO DIVERSITY AND EQUAL EMPLOYMENT OPPORTUNITY:* NIH/NLM encourages the application and nomination of qualified women, minorities, and individuals with disabilities. The U.S. government does not discriminate in employment based on race, color, religion, sex (including sexual orientation, pregnancy, and gender identity), national origin, political affiliation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. NIH/NLM will provide reasonable accommodations to applicants with disabilities as appropriate. If you require reasonable accommodation during any part of the application and hiring process, please notify us. *DHHS, NIH, and NLM are equal opportunity employers*

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Save the date: eLex 2023, 27–29 June 2023
by Ondřej Matuška 19 Sep '22

19 Sep '22

The eighth biennial conference *eLex 2023* electronic lexicography in the 21st century will be held in Brno, Czech Republic, 27–29 June 2023. The topic of this conference is: Invisible lexicography. Save the date and follow the conference on the website, Twitter and Facebook to get updates. More information will be provided in the next couple of days. https://elex.link/elex2023 https://twitter.com/elex_conference www.facebook.com/elexconference We are looking forward to meeting you in Brno. Ondřej Matuška (on behalf of the eLex 2023 organising committee)

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Failed to post position
by Nikolay Babakov 19 Sep '22

19 Sep '22

Hello! I have tried to post the Ph.D. position "PhD position in NL4XAI project (Universitat Autònoma de Barcelona-UAB, Spain)" but failed twice. I get the notification, that the message has been successfully sent, but nothing happens afterward. What should I do? Best regards, Nikolay Babakov

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PhD position in NL4XAI project (Universitat Autònoma de Barcelona-UAB, Spain)
by bbkhse＠gmail.com 19 Sep '22

19 Sep '22

A PhD position is offered within the framework of NL4XAI: Interactive Natural Language Technology for Explainable Artificial Intelligence, a project funded by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 860621. PhD research topic: Argumentation-based Multi-agent Recommender System Host institution: Agencia Estatal del Consejo Superior de Investigaciones Científicas- CSIC (Spain), Barcelona-Spain. Required Degree: Degree in Computer Science (or similar), Master degree in Artificial Intelligence, Computer Science or equivalent providing access to a PhD program. 📆 Deadline for application: October 5, 2022 at 23h59 CET (UCT + 01:00) All details are available at: https://nl4xai.eu/open_position/esr72022-argumentation-based-multi-agent-re… NL4XAI is a European Training Network (ETN) project, which will train 11 creative, entrepreneurial and innovative early-stage researchers (ESRs), who will face the challenge of making Artificial Intelligence (AI) self-explanatory and thus contribute to translating knowledge into products and services for economic and social benefit, with the support of Explainable AI (XAI) systems. The focus of NL4XAI is in the automatic generation of interactive explanations in natural language, just as humans naturally do, and as a complement to visualization tools. As a result, ESRs are expected to leverage the usage of AI models and techniques even by non-expert users. The NL4XAI consortium is made up of 19 partners and beneficiaries from 6 different European countries (France, Malta, Poland, Spain, The Netherlands and the United Kingdom). The consortium is coordinated by the Research Centre in Intelligent Technologies of the Univ. of Santiago de Compostela (CiTIUS-USC) and the partners correspond to 2 national R&D centres (IIIA-CSIC and CNRS-LORIA), 11 universities (Univ. Aberdeen, TU Delft, Univ. Malta, Utrecht Univ., Univ. Twente, Univ. Lorraine, Univ. Dundee, Univ. Autònoma de Barcelona, Univ. Santiago de Compostela, Warsaw Univ. of Technology and Maastricht University) and 6 private companies (Indra, Accenture, Orange, Wizenoze, Arria and Info Support). Each ESR will work in an individual research project in a different host institution and will participate in academic and inter-sectoral secondments at the premises of other NL4XAI’s members. We look for outstanding, motivated and team-spirited candidates to carry out a PhD within the NL4XAI ETN and who will get unique international and inter-sectoral training from prominent European researchers (from both academy and industry). Young researchers willing to work on Explainable AI are encouraged to apply. ralucasilvana.tomoni(a)usc.es

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Job: Research Associate – Natural Language Processing @ UCREL, Lancaster University
by Mo El-Haj 19 Sep '22

19 Sep '22

[in plain text] School of Computing and Communications, Lancaster University Salary: £29,619 to £34,308 Closing Date: Friday 30 September 2022 Interview Date: Wednesday 19 October 2022 Reference: 0978-22 Post URL: https://hr-jobs.lancs.ac.uk/Vacancy.aspx?ref=0978-22 Research Associate – Natural Language Processing Salary: Grade 6 £29,619 to £34,308 The School of Computing and Communications (SCC) within Lancaster University’s Faculty of Science and Technology, is seeking to appoint a Research Associate (RA) to work on research project on Natural Language Processing (NLP) for Canadian Annual Report Extraction (CARE) project. CARE is funded by the Canadian Mitacs (https://www.mitacs.ca/) and HEC Montreal (https://www.hec.ca/en/). Working together with project partners at HEC Montreal (led by Dr Kim Trottier), and Representatives from Chartered Professional Accountants (CPA) of Canada, the RA will develop novel NLP Python tool with techniques to automatically detect structure and extract from PDF annual reports, assess readability and sentiment. The post is based in Lancaster, UK. With CARE, users can upload the PDF of an annual report, run the program, and receive an output consisting of a set of disaggregated text files, one for each section of the annual report. These text files can be useful to investors, regulators, and researchers for performing text analysis. For example, an investor may want to examine a specific section that is relevant to their analysis, such as the chairman’s message or the auditor’s report. A regulator may be interested in assessing climate risk disclosure from the MD&A of all Oil and Gas companies. A researcher exploring goodwill impairment could extract and analyse only the notes on impairments for the firms in their sample. The gains from using CARE are not only in terms of transforming PDF files to text format, but also through an ability to process a large sample of annual reports all at once. While users of CARE can develop and apply their own Natural Language Processing (NLP) algorithms to the disaggregated text files, CARE provides some of the more common metrics for quick analysis. The following information is produced for each text file: readability scores, tone measures, causal language metrics, and word-frequency counts, where the latter (frequency counts) can be tailored to include key words that are relevant to the user. In addition to being efficient, capital markets should strive to provide a level playing field. Institutional investors are able to create their proprietary, in-house programs that extract and analyse the narrative portion of annual reports. CARE brings this functionality to the rest of market participants, through a simple, open-source tool. By supporting the development of CARE, Canadian regulators are positioning themselves to be early-movers in making annual report narratives accessible to a growing set of digital users among their constituents. The RA will be part of an internationally recognised centre of expertise for corpus-based natural language processing (UCREL), and will work directly with Dr Mo El-Haj in SCC at Lancaster University and Dr Kim Trottier in the department of Accounting at HEC Montreal. For more details, please see the associated job description and person specification for this position. Potential candidates can also make informal enquiries to Dr Mo El-Haj (m.el-haj(a)lancaster.ac.uk) and Dr Kim Trottier (kim.trottier(a)hec.ca). This is a 50% part-time position expected to start in November 2022, and the RA will join on an indefinite contract, however the role remains contingent on external funding, which for this position which for this position ends 30th October 2023. Lancaster University are committed to family-friendly and flexible working policies on an individual basis. The School is also an Athena Swan Bronze Award holder, driving good employment practice and initiatives to address gender inequalities in Computing higher education and research. We welcome applications from people in all diversity groups. Best wishes, Mo ————————————————————- Dr Mo El-Haj NLP Lecturer, School of Computing and Communications, Lancaster University, UK https://www.lancaster.ac.uk/staff/elhaj @DocElhaj

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Open position for the analysis of Church Slavonic texts
by Lendvai, Piroska 18 Sep '22

18 Sep '22

The Bavarian Academy of Sciences and Humanities is offering for the externally funded project "QuantiSlav" as of October 1, 2022 a Post-Doc or Master’s level position (m/f/d) E 13 TV-L | part-time (75 %) Provided that the corresponding third-party funds are made available, the employment can take place maximally until the end of the project (September 30, 2025), if the corresponding conditions are met. Place of employment is Munich. The BAdW conducts innovative long-term research in the Humanities and Natural Sciences. It networks scholars internationally and interdisciplinarily, impacts politics and society with its expertise, promotes young scientists and informs the public about current scientific findings. Duties of this position include: - Creating learning materials via digital means and quantitative methods for the analysis of Church Slavonic texts, e.g., in Jupyter notebook format. - Teaching language technology for text-based historical research and data skills at (online) block seminars - Applying language technology methods for the analysis of Slavic medieval writing, e.g. for dating and localization of texts from digital collections of different periods and regions of the 'Slavia Orthodoxa’ - Publishing and presenting scientific papers. Your profile: - Completed university studies in computational linguistics or natural language processing or another relevant technical area or have equivalent expertise, - PhD desirable - Experience in teaching and historical text processing desirable - Knowledge of at least one Slavic language, as well as German or English - Team player - Willing to make regular regular business trips. What we offer: - Diverse fields of development and challenging tasks with a high degree of personal responsibility and creative freedom - Professional development through regular and wide-ranging training opportunities - Attractive work-life balance thanks to flexible working hours and the opportunity to work on a mobile basis - Attractive social benefits: e.g. a company pension scheme, discounted tickets for local public transport and capital-forming benefits. The BAdW is a member of the Diversity Charter and is committed to the diversity of its employees. We support the compatibility of work, family and care. Equal opportunities are of particular importance to the Academy. People with disabilities are given preference in employment if they have equivalent qualifications. The Academy is characterized by the diversity of its employees and welcomes applications from all qualified candidates, regardless of age, gender, sexual orientation, religion, ideology or ethnic origin. By submitting your online application, you confirm that you have read the information sheet on data protection and consent to the collection of personal data as part of your application to the Bavarian Academy of Sciences and Humanities. We look forward to receiving your application, sent as a single PDF file (max. 5 MB) to bewerbungen(a)badw.de. If you have questions about the application process, please contact Ms. Balk/Mrs. Wagner (089/23031-1137 or -1327). Your questions regarding the content of the position will be answered by Dr. Piroska Lendvai (piroska.lendvai(a)badw-muenchen.de).

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Argument Mining workshop (17 October, hybrid, COLING) - scholarships for online participation
by Gabriella Lapesa 17 Sep '22

17 Sep '22

Dear all, The Argument Mining workshop will take place in a hybrid format on October 17, co-located with COLING: https://argmining-org.github.io/2022/ <https://argmining-org.github.io/2022/> We are very happy to announce that we will award scholarships (100 USD, covering early bird deadline for online participation) to selected workshop attendees who have no/limited funding). We ask you to help us reach as many potential applicants as possible (also master students, who have no access to funding but for whom attending such a workshop could be of great inspiration). The link to apply (with more details) is https://docs.google.com/forms/d/1L7WjDSMCGZ8jLX4jvqMWcbJjQ_eTPtEP4Pm8fQHAKsc . <https://docs.google.com/forms/d/1L7WjDSMCGZ8jLX4jvqMWcbJjQ_eTPtEP4Pm8fQHAKsc> Important detail: application deadline is September 22 and the notification date is September 23 (we are aware this is tight but we could settle the budget only now, and early bird deadline is coming up soon, September 25). Thanks for your help disseminating this! Best, Gabriella, Jodi, Yohan, and Sougata (Apologies for cross-posting)

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Postdoctoral Researcher in Natural Language Processing and statistical learning for Health
by Mathieu Constant 17 Sep '22

17 Sep '22

Postdoctoral Researcher in Natural Language Processing and statistical learning for Health The Université de Lorraine (France) invites applications for a postdoctoral Researcher in Natural Language Processing and statistical learning for Health. The position is attached to a new scientific project involving three research units specialized in natural language processing (Research Center for Computer Processing and Analysis of the French Language - ATILF), applied mathematics (Mathematics Research Institute - IECL) and cancer (Research Center for Automatic Control - CRAN). The main objective is to propose new methodologies and an innovative framework for the development of personalized medicine of low-grade brain tumors based on the latest advances in natural language processing and statistical learning. The research will investigate methods to automatically retrieve relevant information based on medical data about patients as well as scientific data publications. The precise research subject within this framework is open to discussion. Terms and tenure This two-year position will be based at the ATILF, Research Center for Computer Processing and Analysis of the French Language (Nancy, France). The duration can not exceed 24 months. The ATILF (https://www.atilf.fr/laboratoire/presentation-english/ <https://www.atilf.fr/laboratoire/presentation-english/>) is a research unit in (computational) linguistics, including expertise in natural language processing and terminology. Within the framework of multidisciplinary activities, the recruited researcher will be required to interact frequently with two other partner research centers of the project, the IECL and the CRAN, also located in Nancy, as well as to the neuro-oncology department of the regional hospital (CHRU) of Nancy. The target start date for the position is flexible and depends on the availability of the candidate, in the limit of the beginning of 2023 (to be discussed). Salary depends on experience. How to apply Applicants are requested to submit the following materials: A cover letter applying for the position Full CV and list of publications Academic transcripts (unofficial versions are fine) Applications will be considered as they arise. PhD students planning to defend before the end of 2022 are very welcome. Applications are only accepted through email. All documents must be sent to Mathieu Constant (Mathieu.Constant(a)univ-lorraine.fr <mailto:Mathieu.Constant@univ-lorraine.fr>), Marianne Clausel (marianne.clausel(a)univ-lorraine.fr <mailto:marianne.clausel@univ-lorraine.fr>) and Hélène Dumond (helene.dumond(a)univ-lorraine.fr <mailto:helene.dumond@univ-lorraine.fr>). Job location Nancy, France Requirements PhD in natural language processing, computer science, machine learning or applied mathematics (PhD from the Université de Lorraine are excluded). Skills Expert knowledge of Natural language processing Good knowledge of statistical learning Good programming skills Experience in the interaction with biologists and clinicians Working in a multidisciplinary team

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Call for Participation: AfriSenti-SemEval Shared Task 12
by Nedjma OUSIDHOUM 16 Sep '22

16 Sep '22

Dear Colleagues, Apologies for cross-posting. We are glad to announce the first SemEval shared task targeting African low-resource languages, AfriSenti-SemEval, Task 12. The AfriSenti-SemEval Shared Task 12 is based on a collection of humanly annotated Twitter datasets in 16 African languages (all low resource) for sentiment classification. This year, we have three sub-tasks, from which the participants can choose one or more tasks depending on their preference. Task A: Monolingual Sentiment Classification Given training data in a target language, determine the polarity of a tweet in the target language (positive, negative, or neutral). If a tweet For messages conveying both a positive and negative sentiment, whichever is the stronger sentiment should be chosen. This sub-task covers 13 languages namely, Hausa, Yoruba, Igbo, Nigerian_Pidgin, Amharic, Algerian Arabic, Kinyarwanda, Twi, Mozambican Portuguese, Swahili, Setswana, isiZulu, Moroccan Arabic/Darija. Task B: Multilingual Sentiment Classification Given combined training data from 13 African languages, determine the polarity of a tweet in the target language (positive, negative, or neutral). Task C: Zero-Shot Sentiment Classification Given unlabeled tweets in three African languages (Oromo, Tigrinya, and Xithonga), leverage any or all of the available training datasets in Subtasks A and B to determine the sentiment of a tweet in the two target languages is positive, negative, or neutral. Helpful Links: - Competition: https://codalab.lisn.upsaclay.fr/competitions/7320 - AfriSenti: https://afrisenti-semeval.github.io/ - Twitter: https://twitter.com/AfriSenti2023 <https://twitter.com/AfriSenti2023> Prize: The afriSenti-SemEval competition has a prize and will be awarded to the best performing team in each of the three sub-tasks. - African League: To encourage African participation, this league is for teams with at least one African. - Master's and Undergraduate League: This league is dedicated to master and undergraduate students only. - Worldwide League: Be a participant from any country. Important Dates: - Training data ready - 11 September 2022 - Evaluation Starts - 10 January 2023 - Evaluation End - 31 January 2023 - System Description Paper Due - February 2023 - SemEval workshop Summer 2023 - (co-located with a major NLP conference) Task Organizers: Shamsuddeen Hassan Muhammad, Seid Muhie Yimam, Idris Abdulmumin, Ibrahim Sa’id, Ahmad, David Ifeoluwa Adelani, Abinew Ali Ayele, Vukosi Marivate, Sebastian Ruder, Saif M. Mohammad, Nedjma Ousidhoum, Meriem Beloucif, Tadesse Destaw Belay

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Call for abstracts: CL poster session at the 45th meeting of the German Linguistic Society (DGfS)
by Rainer Osswald 16 Sep '22

16 Sep '22

CALL FOR ABSTRACTS We would like to invite the submission of abstracts for the computational linguistics poster session of the 45th annual meeting of the German Linguistic Society (DGfS) hosted by the University of Cologne. Since the meeting brings together numerous subfields of linguistics, this is an opportunity to share your work with colleagues both in and out of the computational linguistics field. We invite submissions from all areas of computational linguistics and natural language processing, ranging from machine translation and information retrieval to speech and dialogue systems and cognitive modeling. We especially encourage students and junior researchers to participate. The poster session is organized by the Special Interest Group on Computational Linguistics of the DGfS (dgfs.de/cl). Conference homepage: https://dgfs2023.uni-koeln.de/ DATES - Abstract submission due: October 28, 2022 - Notification of acceptance: November 4, 2022 - Short abstract (for conference website/brochure) due: November 18, 2022 - Conference dates: March 8-10, 2023 SUBMISSION One page abstract (A4) in PDF format (12pt). Submissions can be in German or English. Please submit your abstract via email to: rainer.osswald(a)hhu.de -- Dr. Rainer Osswald Department of Computational Linguistics Heinrich-Heine-Universität Düsseldorf Universitätsstraße 1 40225 Düsseldorf, Germany https://user.phil.hhu.de/osswald/

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