Call for Papers
https://reneuir.org/
The ReNeuIR Workshop will be held at SIGIR 2022 and, as with the main conference, is planned as a hybrid event—in person in Madrid, Spain, with support for remote participation.
In addition to the workshop, we have initiated a process for authors of selected papers to submit an extended version of their work to a special issue of an international journal. We will release more information as we obtain the necessary approval.
## Topics of Interest
We welcome submissions on the following topics, including but not limited to:
- Novel NIR models that reach competitive quality but are designed to provide fast training or fast inference;
- Efficient NIR models for decentralized IR tasks such as conversational search;
- Strategies to speed up training or inference of existing NIR models;
- Sample-efficient training of NIR models;
- Efficiency-driven distillation, pruning, quantization, retraining, and transfer learning;
- Empirical investigation and justification of the complexity of existing NIR models through an analysis of quality, interpretability, or robustness; and
- Evaluation protocols for efficiency in NIR.
## Important Dates
- Submission deadline: Friday, April 29, 2022
- Notification of acceptance: Monday, May 23, 2022
- Workshop: Friday, Jul 15, 2022
All deadlines are 11.59 pm UTC -12h (“anywhere on Earth”).
## Submission Guidelines, Anonymity, and Desk Rejection Policy
We adopt and observe the submission guidelines, anonymity, and desk rejection policies of SIGIR 2022 Full Paper Track. Authors must refer to the SIGIR Call for Full Papers for more information.
Submissions must be anonymous and should be submitted electronically via EasyChair (https://easychair.org/conferences/?conf=reneuir2022).
https://reneuir.org/
The ReNeuIR Workshop will be held at SIGIR 2022 and, as with the main conference, is planned as a hybrid event—in person in Madrid, Spain, with support for remote participation.
In addition to the workshop, we have initiated a process for authors of selected papers to submit an extended version of their work to a special issue of an international journal. We will release more information as we obtain the necessary approval.
## Topics of Interest
We welcome submissions on the following topics, including but not limited to:
- Novel NIR models that reach competitive quality but are designed to provide fast training or fast inference;
- Efficient NIR models for decentralized IR tasks such as conversational search;
- Strategies to speed up training or inference of existing NIR models;
- Sample-efficient training of NIR models;
- Efficiency-driven distillation, pruning, quantization, retraining, and transfer learning;
- Empirical investigation and justification of the complexity of existing NIR models through an analysis of quality, interpretability, or robustness; and
- Evaluation protocols for efficiency in NIR.
## Important Dates
- Submission deadline: Friday, April 29, 2022
- Notification of acceptance: Monday, May 23, 2022
- Workshop: Friday, Jul 15, 2022
All deadlines are 11.59 pm UTC -12h (“anywhere on Earth”).
## Submission Guidelines, Anonymity, and Desk Rejection Policy
We adopt and observe the submission guidelines, anonymity, and desk rejection policies of SIGIR 2022 Full Paper Track. Authors must refer to the SIGIR Call for Full Papers for more information.
Submissions must be anonymous and should be submitted electronically via EasyChair (https://easychair.org/conferences/?conf=reneuir2022).
The School of Informatics, University of Edinburgh, is thrilled to
announce a PhD scholarship funded by Google DeepMind.
The scholarship covers tuition fees (at the Home/International tuition
fee rate), provides an annual stipend of £18,622 per annum (for 3.5
years full time study) and provides a research training and support
grant. The student will be supervised by Dr. Mirella Lapata and will
also benefit from mentoring from DeepMind staff during their period of
study.
Applicants would be expected to work on a topic drawn from the
following research areas:
- multimodal natural language understanding and generation
- long-form and retrieval-augmented text generation
- multilingual generation
Applicants wishing to apply for the scholarship should meet one OR
both of the following criteria:
- are resident of a country and/or region underrepresented in AI;
- identify as women including cis and trans people and non-binary or
gender fluid people who identify in a significant way as women or
female;
- and/or identify as Black or other minority ethnicity.
The successful candidate will have a good honours degree or equivalent
in artificial intelligence, computer science, machine learning, or a
related discipline; or have a breadth of relevant experience in
industry/academia/public sector, etc. They will have strong
programming skills and previous experience in natural language
processing.
If you have further questions, please contact Dr. Mirella Lapata:
mlap@inf.ed.ac.uk.
To apply, please follow the instructions at:
http://www.inf.ed.ac.uk/postgraduate/apply.html
As your research area, please select "Informatics: ILCC: Language
Processing, Speech Technology, Information Retrieval, Cognition". On
the application form under "Research Project", please state "DeepMind
Scholarship".
announce a PhD scholarship funded by Google DeepMind.
The scholarship covers tuition fees (at the Home/International tuition
fee rate), provides an annual stipend of £18,622 per annum (for 3.5
years full time study) and provides a research training and support
grant. The student will be supervised by Dr. Mirella Lapata and will
also benefit from mentoring from DeepMind staff during their period of
study.
Applicants would be expected to work on a topic drawn from the
following research areas:
- multimodal natural language understanding and generation
- long-form and retrieval-augmented text generation
- multilingual generation
Applicants wishing to apply for the scholarship should meet one OR
both of the following criteria:
- are resident of a country and/or region underrepresented in AI;
- identify as women including cis and trans people and non-binary or
gender fluid people who identify in a significant way as women or
female;
- and/or identify as Black or other minority ethnicity.
The successful candidate will have a good honours degree or equivalent
in artificial intelligence, computer science, machine learning, or a
related discipline; or have a breadth of relevant experience in
industry/academia/public sector, etc. They will have strong
programming skills and previous experience in natural language
processing.
If you have further questions, please contact Dr. Mirella Lapata:
mlap@inf.ed.ac.uk.
To apply, please follow the instructions at:
http://www.inf.ed.ac.uk/postgraduate/apply.html
As your research area, please select "Informatics: ILCC: Language
Processing, Speech Technology, Information Retrieval, Cognition". On
the application form under "Research Project", please state "DeepMind
Scholarship".
Dear all,
The research group DRX of The German Research Center for AI in Berlin, under the direction of Prof. Dr. Gesche Joost, investigates smart technologies from a designerly perspective. For an upcoming research project, we are looking for a researcher (who could be a PhD candidate or a post-doc) to explore human-in-the-loop approaches to optimize LLMs for new AI products. The deadline is October 20.
Please find more details at the URL: https://jobs.dfki.de/en/vacancy/researcher-m-f-d-in-drx-539334.html
The research group DRX of The German Research Center for AI in Berlin, under the direction of Prof. Dr. Gesche Joost, investigates smart technologies from a designerly perspective. For an upcoming research project, we are looking for a researcher (who could be a PhD candidate or a post-doc) to explore human-in-the-loop approaches to optimize LLMs for new AI products. The deadline is October 20.
Please find more details at the URL: https://jobs.dfki.de/en/vacancy/researcher-m-f-d-in-drx-539334.html
PhD position: Machine Learning for Natural Languages and other sequence data
========================================================= ====
(Computer Science, Computational Linguistics, Physics or similar)
The research group is focusing on getting a deeper understanding of how modern deep learning methods can be applied to natural languages or other sequence papers. Our recent achievements include a best paper award at COLING 2022 and a best theme paper award at ACL 2023. We offer a PhD position that is topically open and should have a strong focus on applying machine learning techniques to natural language data or other sequence data (e.g., string representations of chemical compounds).
The ideal candidate for the position would have:
1. Excellent knowledge of machine learning and deep learning
2. Excellent programming skills
3. Masters degree in Computer Science, Computational Linguistics, Physics, or similar
Salary: The PhD position will be 75% of full time on the German E13 scale (TV-L) which is about 3144€ per month before tax and social security contributions. The appointments will be for three years with a possible extension at 50%.
About the department: The department of Language Science and Technology is one of the leading departments in the speech and language area in Europe. The flagship project at the moment is the CRC on Information Density and Linguistic Encoding. It also runs a significant number of European and nationally funded projects. In total, it has seven faculty and around 50 postdoctoral researchers and PhD students. The department is part of the Saarland Informatics Campus. With 900 researchers, two Max Planck institutes and the German Research Center for Artificial Intelligence, it is one of the leading locations for Informatics in Germany and Europe.
How to apply: Please send us a letter of motivation, a research plan (max one page), your CV, your trannoscripts, if available a list of publications, and the names and contact information of at least two references, as a single PDF or a link to a PDF if the file size is more than 5 MB.
Please apply latest by November 20th, 2023. Earlier applications are welcome and will be processed as they come in.
Contact: Applications and any further inquiries regarding the project should be directed to dietrich.klakow at lsv.uni-saarland.de
========================================================= ====
(Computer Science, Computational Linguistics, Physics or similar)
The research group is focusing on getting a deeper understanding of how modern deep learning methods can be applied to natural languages or other sequence papers. Our recent achievements include a best paper award at COLING 2022 and a best theme paper award at ACL 2023. We offer a PhD position that is topically open and should have a strong focus on applying machine learning techniques to natural language data or other sequence data (e.g., string representations of chemical compounds).
The ideal candidate for the position would have:
1. Excellent knowledge of machine learning and deep learning
2. Excellent programming skills
3. Masters degree in Computer Science, Computational Linguistics, Physics, or similar
Salary: The PhD position will be 75% of full time on the German E13 scale (TV-L) which is about 3144€ per month before tax and social security contributions. The appointments will be for three years with a possible extension at 50%.
About the department: The department of Language Science and Technology is one of the leading departments in the speech and language area in Europe. The flagship project at the moment is the CRC on Information Density and Linguistic Encoding. It also runs a significant number of European and nationally funded projects. In total, it has seven faculty and around 50 postdoctoral researchers and PhD students. The department is part of the Saarland Informatics Campus. With 900 researchers, two Max Planck institutes and the German Research Center for Artificial Intelligence, it is one of the leading locations for Informatics in Germany and Europe.
How to apply: Please send us a letter of motivation, a research plan (max one page), your CV, your trannoscripts, if available a list of publications, and the names and contact information of at least two references, as a single PDF or a link to a PDF if the file size is more than 5 MB.
Please apply latest by November 20th, 2023. Earlier applications are welcome and will be processed as they come in.
Contact: Applications and any further inquiries regarding the project should be directed to dietrich.klakow at lsv.uni-saarland.de
The NLP group at Linköping University, Sweden, is now hiring a PhD student for research on multilingual LLMs for lower-resourced languages!
For this PhD position, you will work within the TrustLLM project, an EU-funded Horizon Europe project on developing open, trustworthy, and sustainable LLMs, initially targeting the Germanic languages. It involves consortium partners from Denmark, Germany, Iceland, The Netherlands, Norway, and Sweden. Specific research topics include:
tokenization and embedding alignment techniques
addressing grammatical correctness and bias in pre-training
benchmarking and evaluation
You will also participate in the Graduate School in Computer Science (CUGS) at Linköping University.
Your PhD supervisors will be Marcel Bollmann and Marco Kuhlmann. This PhD position is a fully-funded, full-time, salaried position with attractive employee benefits and pension contributions.
For more information about the position and a link to the application system, please see
https://www.ida.liu.se/divisions/aiics/nlp/phd-student-trustllm/
You are welcome to contact me or Marco for additional information.
The application deadline is 2023-11-21.
Best wishes,
Marcel Bollmann
For this PhD position, you will work within the TrustLLM project, an EU-funded Horizon Europe project on developing open, trustworthy, and sustainable LLMs, initially targeting the Germanic languages. It involves consortium partners from Denmark, Germany, Iceland, The Netherlands, Norway, and Sweden. Specific research topics include:
tokenization and embedding alignment techniques
addressing grammatical correctness and bias in pre-training
benchmarking and evaluation
You will also participate in the Graduate School in Computer Science (CUGS) at Linköping University.
Your PhD supervisors will be Marcel Bollmann and Marco Kuhlmann. This PhD position is a fully-funded, full-time, salaried position with attractive employee benefits and pension contributions.
For more information about the position and a link to the application system, please see
https://www.ida.liu.se/divisions/aiics/nlp/phd-student-trustllm/
You are welcome to contact me or Marco for additional information.
The application deadline is 2023-11-21.
Best wishes,
Marcel Bollmann
Marcel Bollmann
About me | Marcel Bollmann
Associate Professor in Natural Language Processing at Linköping University, Sweden. Previously worked at Jönköping University, University of Copenhagen, and Ruhr-Universität Bochum. Main research areas include NLP for historical documents, multilinguality…
1 PhD Position on industrial applications of Large Language Models at the Technische Hochschule Augsburg
We invite applications for a fully funded PhD position at the University of Applied Sciences in Augsburg ("Technische Hochschule Augsburg", full-time, TV-L E13 on the German federal wage agreement scheme) on industrial applications of Large Language Models in the project "CHIASM" ("Chancenreiche industrielle Anwendungen für vortrainierte Sprachmodelle").
The University of Applied Sciences in Augsburg is an important center fueling innovation in the region and offers plenty of opportunities to collaborate with local companies to integrate the latest technologies in real use cases. We are committed to a collegial and family-friendly
work environment and flexible working hours.
You can find the call here:
https://karriere.hs-augsburg.de/Wissenschaftlicher-Mitarbeiterin-mwd-mit-Promotionsziel-de-j786.html
Please apply at your earliest convenience but no later than Nov 22nd. I am happy to answer questions about the position ( alessandra.zarcone@tha.de ).
Best
Alessandra Zarcone
We invite applications for a fully funded PhD position at the University of Applied Sciences in Augsburg ("Technische Hochschule Augsburg", full-time, TV-L E13 on the German federal wage agreement scheme) on industrial applications of Large Language Models in the project "CHIASM" ("Chancenreiche industrielle Anwendungen für vortrainierte Sprachmodelle").
The University of Applied Sciences in Augsburg is an important center fueling innovation in the region and offers plenty of opportunities to collaborate with local companies to integrate the latest technologies in real use cases. We are committed to a collegial and family-friendly
work environment and flexible working hours.
You can find the call here:
https://karriere.hs-augsburg.de/Wissenschaftlicher-Mitarbeiterin-mwd-mit-Promotionsziel-de-j786.html
Please apply at your earliest convenience but no later than Nov 22nd. I am happy to answer questions about the position ( alessandra.zarcone@tha.de ).
Best
Alessandra Zarcone
karriere.hs-augsburg.de
Stellenangebot Wissenschaftliche:r Mitarbeiter:in (m/w/d) mit Promotionsziel an der Hochschule für angewandte Wissenschaften Augsburg…
Fakultät für Informatik in Augsburg
Hi,
I'm recruiting PhD students for my group at the University of Sydney. See this page for details:
https://www.jkk.name/students/recruiting-phd/
I have funding for projects in a wide range of NLP topics.
Note that, unlike the central application process for many PhD programs, students should apply directly to me. I have already started reading applications, so students should contact me as soon as possible.
Thanks!
Jonathan Kummerfeld
I'm recruiting PhD students for my group at the University of Sydney. See this page for details:
https://www.jkk.name/students/recruiting-phd/
I have funding for projects in a wide range of NLP topics.
Note that, unlike the central application process for many PhD programs, students should apply directly to me. I have already started reading applications, so students should contact me as soon as possible.
Thanks!
Jonathan Kummerfeld
Jonathan K. Kummerfeld
Recruiting: PhD
Work with me on NLP at the University of Sydney!
My primary recruiting timeline is:
Read applications in late October Interview and make offers in November I am open to applications from outstanding students at any time, but my expectations are higher outside…
My primary recruiting timeline is:
Read applications in late October Interview and make offers in November I am open to applications from outstanding students at any time, but my expectations are higher outside…
A one-year Research Fellowship ("assegno di ricerca") on the analysis and automatic recognition of commensal activities is available at the University of Genoa within the COmputational Models of COmmensality for artificial Agents (COCOA) project, funded by the Italian Ministry of University and Research. The project aims to investigate human-human interactions in a commensal setting using state-of-the-art machine learning methods, as well as to develop artificial commensal companions (e.g., social robots) capable of engaging with human commensals.
The fellow will be responsible for collecting data, designing, and developing models for the analysis and recognition of commensal activities at the individual level (e.g., detecting activities such as chewing and drinking, gaze direction) and group level (e.g., analyzing social interactions), using video data and deep/machine learning techniques.
Requirements: Candidates must hold a Master’s degree in Computer Science, Cognitive Science, Data Science, Robotics, or related areas. Previous experience in machine/deep learning applied to computer vision will be highly valued.
Salary: 23K Euro
Location: University of Genoa, Genoa, Italy
Duration: 1 year
For more information, please contact: Radoslaw Niewiadomski (radoslaw.niewiadomski@dibris.unige.it)
References:
https://dl.acm.org/doi/abs/10.1145/3536221.3556566
https://www.frontiersin.org/articles/10.3389/fcomp.2022.909844/full
The fellow will be responsible for collecting data, designing, and developing models for the analysis and recognition of commensal activities at the individual level (e.g., detecting activities such as chewing and drinking, gaze direction) and group level (e.g., analyzing social interactions), using video data and deep/machine learning techniques.
Requirements: Candidates must hold a Master’s degree in Computer Science, Cognitive Science, Data Science, Robotics, or related areas. Previous experience in machine/deep learning applied to computer vision will be highly valued.
Salary: 23K Euro
Location: University of Genoa, Genoa, Italy
Duration: 1 year
For more information, please contact: Radoslaw Niewiadomski (radoslaw.niewiadomski@dibris.unige.it)
References:
https://dl.acm.org/doi/abs/10.1145/3536221.3556566
https://www.frontiersin.org/articles/10.3389/fcomp.2022.909844/full
--
Radoslaw Niewiadomski
Tenure-Track Assistant Professor
University of GenoaACM Conferences
Towards Commensal Activities Recognition | Proceedings of the 2022 International Conference on Multimodal Interaction
Dear all,
this week Thursday and Friday (16.-17. November) we will host an event at GESIS Cologne focusing on Harmful Online Communication, such as hatespeech and disinformation. We have invited expert speakers to present their research results or discuss with us about methods and challenges in this area.
We arranged for most parts of the event to be streamed online via Zoom. You can register here for free online: attendance: https://www.gesis.org/en/research/conferences/gesis-conferences/conference-on-harmful-online-communication-choc2023
Greetings from
Katrin Weller, Christina Dahn, Indira Sen, Pascal Siegers (and the entire organizing team)
this week Thursday and Friday (16.-17. November) we will host an event at GESIS Cologne focusing on Harmful Online Communication, such as hatespeech and disinformation. We have invited expert speakers to present their research results or discuss with us about methods and challenges in this area.
We arranged for most parts of the event to be streamed online via Zoom. You can register here for free online: attendance: https://www.gesis.org/en/research/conferences/gesis-conferences/conference-on-harmful-online-communication-choc2023
Greetings from
Katrin Weller, Christina Dahn, Indira Sen, Pascal Siegers (and the entire organizing team)
www.gesis.org
Conference on Harmful Online Communication (CHOC2023)
GESIS Leibniz Institut für Sozialwissenschaften
NLP Fully Funded PhD position at Ulster University, UK
two fully funded position for 3 years in Social Network Analysis
https://www.ulster.ac.uk/doctoralcollege/find-a-phd/1577710
Speech and Language Disorder,
https://www.ulster.ac.uk/doctoralcollege/find-a-phd/1577271
two fully funded position for 3 years in Social Network Analysis
https://www.ulster.ac.uk/doctoralcollege/find-a-phd/1577710
Speech and Language Disorder,
https://www.ulster.ac.uk/doctoralcollege/find-a-phd/1577271
A fully funded PhD position is now available at King’s College London on the project “‘Lost for words’: semantic search in the Find Case Law service of The
National Archives”, a Collaborative Doctoral Award received by King’s College London in collaboration with The National Archives and funded by the London Arts & Humanities Partnership (LAHP). This interdisciplinary project is an exciting opportunity to work
in natural language processing (particularly computational semantics and information retrieval) applied to legal texts and digital humanities.
About the project:
Access to case law is vital for safeguarding the constitutional right of access to justice. It enables members of the public to understand their position when facing litigation and to scrutinise court judgements. Since April 2022,
UK court and tribunal decisions are preserved by The National Archives’ Find Case Law service as freely accessible online public records. This project seeks to improve Find Case Law by enhancing it with meaning-sensitive (semantic) search functionality. It
will study how individuals without legal training use language to navigate court judgments and it will develop tools to facilitate this navigation. In most digital cultural heritage catalogues, while we can search for words within the metadata describing their
records, we cannot search for records based on the meaning of words contained within these records, for example the different words to refer to “knife crime”. Therefore, users’ access to collection is determined by their ability to articulate their information
need precisely. Recent advances in natural language processing unlock new possibilities for querying documents via state-of-the-art semantic search. Incorporating such search capabilities in the Find Case Law collection is crucial for democratising access
to digital collections, helping expose the social impact of how the law is written.
Skills required
Essential:
·
Experience with Natural Language Processing research and applied work, including developing new tools.
·
Interest in working with UK case law for improving access to justice
Desirable:
·
Background in law or legal research.
·
Experience working with digital archives
·
Knowledge of User experience (UX) research
·
Knowledge of lexical semantics.
·
Experience with semantic search.
·
Experience with NLP applied to legal texts.
About application process:
Applicants will need to submit an application for a PhD in Digital Humanities at King’s (https://tinyurl.com/ycxekhzv
) and an application for the LAHP (https://www.lahp.ac.uk/prospective-students/collaborative-doctoral-awards-projects-available/). Both applications
need to be submitted by 26 January 2024 at 5pm.
Application Deadline: 26-Jan-2024
Web Address for Applications:
https://lahp.flexigrant.com/login.aspx?ReturnUrl=https%3a%2f%2flahp.flexigrant.com%2fstartapplication.aspx%3fid%3d12709
For queries specific to the project, please contact the project’s lead supervisor Barbara McGillivray on
barbara.mcgillivray@kcl.ac.uk
National Archives”, a Collaborative Doctoral Award received by King’s College London in collaboration with The National Archives and funded by the London Arts & Humanities Partnership (LAHP). This interdisciplinary project is an exciting opportunity to work
in natural language processing (particularly computational semantics and information retrieval) applied to legal texts and digital humanities.
About the project:
Access to case law is vital for safeguarding the constitutional right of access to justice. It enables members of the public to understand their position when facing litigation and to scrutinise court judgements. Since April 2022,
UK court and tribunal decisions are preserved by The National Archives’ Find Case Law service as freely accessible online public records. This project seeks to improve Find Case Law by enhancing it with meaning-sensitive (semantic) search functionality. It
will study how individuals without legal training use language to navigate court judgments and it will develop tools to facilitate this navigation. In most digital cultural heritage catalogues, while we can search for words within the metadata describing their
records, we cannot search for records based on the meaning of words contained within these records, for example the different words to refer to “knife crime”. Therefore, users’ access to collection is determined by their ability to articulate their information
need precisely. Recent advances in natural language processing unlock new possibilities for querying documents via state-of-the-art semantic search. Incorporating such search capabilities in the Find Case Law collection is crucial for democratising access
to digital collections, helping expose the social impact of how the law is written.
Skills required
Essential:
·
Experience with Natural Language Processing research and applied work, including developing new tools.
·
Interest in working with UK case law for improving access to justice
Desirable:
·
Background in law or legal research.
·
Experience working with digital archives
·
Knowledge of User experience (UX) research
·
Knowledge of lexical semantics.
·
Experience with semantic search.
·
Experience with NLP applied to legal texts.
About application process:
Applicants will need to submit an application for a PhD in Digital Humanities at King’s (https://tinyurl.com/ycxekhzv
) and an application for the LAHP (https://www.lahp.ac.uk/prospective-students/collaborative-doctoral-awards-projects-available/). Both applications
need to be submitted by 26 January 2024 at 5pm.
Application Deadline: 26-Jan-2024
Web Address for Applications:
https://lahp.flexigrant.com/login.aspx?ReturnUrl=https%3a%2f%2flahp.flexigrant.com%2fstartapplication.aspx%3fid%3d12709
For queries specific to the project, please contact the project’s lead supervisor Barbara McGillivray on
barbara.mcgillivray@kcl.ac.uk
King's College London
Digital Humanities Research
Take a PhD in Digital Humanities at King's College London or a joint PhD with the National University of Singapore.
Application for September 2024 is open
https://mobility.smarts-up.fr/
Choose one or our master specialties and apply for a 10 000 euros /year grant
https://paris-gsl.org/applying
Deadline: January 19th 2024 (5 pm Paris time)
https://mobility.smarts-up.fr/
Choose one or our master specialties and apply for a 10 000 euros /year grant
https://paris-gsl.org/applying
Deadline: January 19th 2024 (5 pm Paris time)
Research Fellow (grade 7)
£38,560 - £43,374 per annum
Fixed term for 24 months (2 years) -- with the potential for renewal
School of Computing & Engineering
University of Huddersfield
Application deadline: 31 January 2024
Website for info and application: http://hud.ac/q3m
We have an exciting opportunity for a Research Fellow to join the AI4UTMC research team (ai4utmc.info) within the School of Computing & Engineering, at the University of Huddersfield. The AI4UTMC research team is part of the research Centre on Autonomous and Intelligent Systems (CAIS), that is currently working on a variety of topics involving the design and use of AI techniques, for instance in robotics, healthcare, logistics, and supply chain optimisation. It provides the ideal environment for a researcher interested in the positive impact that AI can have on our society.
We are looking for a dedicated individual to work on the design of AI-based approaches for supporting innovative intelligent urban traffic management and control systems. The research team has great expertise in the field of intelligent traffic control and mobility, and excellent connections with industry and traffic authorities.
The work will entail the design and developments of AI-based techniques, and the experimental evaluation on real-world data provided by project partners. You will help review the available literature, design and develop techniques, collect and analyse data, and generate academic outputs. With a Doctoral qualification in AI or a closely related area, you will have an interest in AI and machine learning applications, and an enquiring and creative approach to challenges. Knowledge in both model-based (e.g., Automated Planning, CP) and data-driven AI will be a nice plus.
You’ll be line managed by Mauro Vallati (www.mvallati.net) and this, according to a completely unbiased pool of experts, is a very nice benefit (particularly if you like beer).
Informal enquiries are welcome to Mauro Vallati via email: m.vallati@hud.ac.uk
For info and application: http://hud.ac/q3m
£38,560 - £43,374 per annum
Fixed term for 24 months (2 years) -- with the potential for renewal
School of Computing & Engineering
University of Huddersfield
Application deadline: 31 January 2024
Website for info and application: http://hud.ac/q3m
We have an exciting opportunity for a Research Fellow to join the AI4UTMC research team (ai4utmc.info) within the School of Computing & Engineering, at the University of Huddersfield. The AI4UTMC research team is part of the research Centre on Autonomous and Intelligent Systems (CAIS), that is currently working on a variety of topics involving the design and use of AI techniques, for instance in robotics, healthcare, logistics, and supply chain optimisation. It provides the ideal environment for a researcher interested in the positive impact that AI can have on our society.
We are looking for a dedicated individual to work on the design of AI-based approaches for supporting innovative intelligent urban traffic management and control systems. The research team has great expertise in the field of intelligent traffic control and mobility, and excellent connections with industry and traffic authorities.
The work will entail the design and developments of AI-based techniques, and the experimental evaluation on real-world data provided by project partners. You will help review the available literature, design and develop techniques, collect and analyse data, and generate academic outputs. With a Doctoral qualification in AI or a closely related area, you will have an interest in AI and machine learning applications, and an enquiring and creative approach to challenges. Knowledge in both model-based (e.g., Automated Planning, CP) and data-driven AI will be a nice plus.
You’ll be line managed by Mauro Vallati (www.mvallati.net) and this, according to a completely unbiased pool of experts, is a very nice benefit (particularly if you like beer).
Informal enquiries are welcome to Mauro Vallati via email: m.vallati@hud.ac.uk
For info and application: http://hud.ac/q3m
PhD and Postdoc at LMU Munich
https://mainlp.github.io/jobs/
https://mainlp.github.io/jobs/
mainlp.github.io
Jobs | MaiNLP research lab
Munich AI & NLP lab
The Laboratoire de Linguistique Formelle (www.llf.cnrs.fr, LLF) is seeking to support applications in linguistics and language sciences to Research Associate positions at the French Centre National de la Recherche Scientifique (cnrs.fr).
CNRS Research Associate positions are full-time permanent positions intended for candidates in their early career. Applicants must hold a PhD by the application deadline. Knowledge of French is not required.
Although CNRS recruits researchers by way of a national competition, applicants are encouraged to select one or more research labs to which they would like to be assigned, and support is crucial for a successful application.
Located at Université Paris Cité (u-paris.fr), the LLF has about 80 members, including 36 permanent faculty members, working on every subfield of linguistics. In recent years, it has extended its focus from formal and theoretical linguistics to domains such as psycholinguistics, sociolinguistics, experimental linguistics, computational linguistics, dialogue, typology, and Sign language linguistics.
The LLF is interested in supporting a limited number of applicants, with an excellent research record and willing to develop a project that would fit the lab's areas of inquiry.
The official call for application will be published on January 10, 2024 with an application deadline of February 9, 2024 (https://www.cnrs.fr/en/competitive-entrance-examinations-researchers-womenmen). Prospective applicants that wish to be supported by the LLF are invited to contact the lab by January 12, sending a CV (including a publication list) and a short denoscription of their research profile to direction.llf@listes.u-paris.fr. Decisions on whether support is granted will be taken by January 16.
CNRS Research Associate positions are full-time permanent positions intended for candidates in their early career. Applicants must hold a PhD by the application deadline. Knowledge of French is not required.
Although CNRS recruits researchers by way of a national competition, applicants are encouraged to select one or more research labs to which they would like to be assigned, and support is crucial for a successful application.
Located at Université Paris Cité (u-paris.fr), the LLF has about 80 members, including 36 permanent faculty members, working on every subfield of linguistics. In recent years, it has extended its focus from formal and theoretical linguistics to domains such as psycholinguistics, sociolinguistics, experimental linguistics, computational linguistics, dialogue, typology, and Sign language linguistics.
The LLF is interested in supporting a limited number of applicants, with an excellent research record and willing to develop a project that would fit the lab's areas of inquiry.
The official call for application will be published on January 10, 2024 with an application deadline of February 9, 2024 (https://www.cnrs.fr/en/competitive-entrance-examinations-researchers-womenmen). Prospective applicants that wish to be supported by the LLF are invited to contact the lab by January 12, sending a CV (including a publication list) and a short denoscription of their research profile to direction.llf@listes.u-paris.fr. Decisions on whether support is granted will be taken by January 16.
Centre national de la recherche scientifique (CNRS)
Accueil CNRS (CNRS)
Acteur majeur de la recherche fondamentale et de l’innovation à l’échelle mondiale, le Centre national de la recherche scientifique (CNRS) est le seul organisme français actif dans tous les domaines scientifiques. Ensemble, les sciences se mettent au service…
Applications are invited for a fully funded PhD candidature in at Leiden Institute of Advanced Computer Science (LIACS), The Netherlands, on the use of Formal Methods to enhance the efficiency, transparency and the understanding of Transformer-based language models.
While large language models (LLMs) have proven successful in many areas of Natural Language Processing, they suffer from high data and resource usage, and display limited generalization capacity in tasks that humans excel at. In this PhD project you will have the opportunity to investigate how formal methods can help in developing more efficient and more transparent models for Natural Language Understanding. Specifically, you will investigate the use of implicit or explicit structural bias in Transformer-based language models to reduce training data and model parameters; additionally, you will look at novel techniques for evaluating models for their generalization capabilities on Natural Language Understanding tasks such as Natural Language Inference, possibly in a multilingual and multimodal setting.
The specific project content is to be decided between the applicants’ interest and the expertise of the supervisor, dr. Gijs Wijnholds.
Topics include (but are not limited to):
- Using logical methods to define task-relevant constraints on LLM finetuning;
- Incorporating structured representations in regularized training of smaller language models;
- Assessing the generalization capacity of Transformer-based models in the context of formal language theory, model probing, Natural Language Inference;
- Evaluation of Natural Language Understanding models in the presence of ambiguity and/or annotator disagreement;
- Understanding multilingual Natural Language Inference in Vision-Language Models;
For the official vacancy text, please see https://www.universiteitleiden.nl/en/vacancies/2023/qw4/23-81914335phd-candidate-formal-methods-in-natural-language-processing
The application deadline is January 13, 2024. The ideal starting date is in March 2024, but can be negotiated depending on circumstances.
For further information feel free to reach out to dr. Gijs Wijnholds (g.j.wijnholds@liacs.leidenuniv.nl).
While large language models (LLMs) have proven successful in many areas of Natural Language Processing, they suffer from high data and resource usage, and display limited generalization capacity in tasks that humans excel at. In this PhD project you will have the opportunity to investigate how formal methods can help in developing more efficient and more transparent models for Natural Language Understanding. Specifically, you will investigate the use of implicit or explicit structural bias in Transformer-based language models to reduce training data and model parameters; additionally, you will look at novel techniques for evaluating models for their generalization capabilities on Natural Language Understanding tasks such as Natural Language Inference, possibly in a multilingual and multimodal setting.
The specific project content is to be decided between the applicants’ interest and the expertise of the supervisor, dr. Gijs Wijnholds.
Topics include (but are not limited to):
- Using logical methods to define task-relevant constraints on LLM finetuning;
- Incorporating structured representations in regularized training of smaller language models;
- Assessing the generalization capacity of Transformer-based models in the context of formal language theory, model probing, Natural Language Inference;
- Evaluation of Natural Language Understanding models in the presence of ambiguity and/or annotator disagreement;
- Understanding multilingual Natural Language Inference in Vision-Language Models;
For the official vacancy text, please see https://www.universiteitleiden.nl/en/vacancies/2023/qw4/23-81914335phd-candidate-formal-methods-in-natural-language-processing
The application deadline is January 13, 2024. The ideal starting date is in March 2024, but can be negotiated depending on circumstances.
For further information feel free to reach out to dr. Gijs Wijnholds (g.j.wijnholds@liacs.leidenuniv.nl).
Vacancy - Data Scientist for Dynamic Scheduling (MJM Marine & Ulster University)
https://bit.ly/MJMMarineKTP2023
https://bit.ly/MJMMarineKTP2023