Forwarded from CS50x Iran
● آغاز ثبت نام دومین دوره CS50 در ایران.
دوره مبانی علوم کامپیوتر هاروارد
برای اطلاعات بیشتر و ثبتنام به آدرس زیر مراجعه کنید:
CS50x.ir/summer2021
@CS50xIran
دوره مبانی علوم کامپیوتر هاروارد
برای اطلاعات بیشتر و ثبتنام به آدرس زیر مراجعه کنید:
CS50x.ir/summer2021
@CS50xIran
*** Call for participation: SCAI QReCC 21 Conversational Question
Answering Challenge***
We are pleased to announce that this year we will be hosting a shared
task on open-domain conversational question answering (QA) co-located
with SCAI 2021 (https://scai.info). The shared task aims to establish a
reliable benchmark for conversational QA and encourage collaboration
between communities working on dialogue response generation, passage
retrieval and reading comprehension.
Web page: https://scai.info/scai-qrecc
Leaderboard: https://www.tira.io/task/scai-qrecc
Registration: https://forms.gle/JFBXZXPtWPqbtLhu8
Register to receive further updates, make leaderboard submissions, get
access to the TIRA forum and keep in touch with other participating teams.
Submission deadline: September 8, 2021
Results announcement: September 30, 2021
Workshop presentations: October 8, 2021
* Task *
Conversational question answering (QA) is one of the core applications
for retrieval-based chatbots. In conversational QA, the task is to
answer a series of contextually-dependent questions like they may occur
in a natural human-to-human conversation. It is also possible to
participate with non-conversational approaches in the conversational
task by using our question rewrites. For more details on question
rewriting see [1].
* Dataset *
The challenge uses the QReCC dataset [1] for evaluation, to appear in
NAACL’21 proceedings. The dataset contains 14K conversations with 81K
question-answer pairs and 54M passages [2]. The passage collection was
constructed by processing 10M web pages from the Common Crawl and the
Wayback Machine [3]. We will use the submitted runs to pull alternative
answers and relevant passages that are discovered by the participating
systems to extend the coverage of the ground truth annotations and
improve the evaluation metrics.
* Evaluation *
The primary evaluation metrics is F1 and EM performance on the QA task.
However, we also, optionally, report MRR and ROUGE for passage retrieval
and question rewriting subtasks to provide better insights on the
performance over the intermediate steps.
* Workshop *
Participating teams will be invited to submit a short notebook paper
detailing their approach for publication in conjunction with the SCAI’21
workshop [4].
* Contact *
scai-qrecc@googlegroups.com
Kind regards,
Organisers of the SCAI QReCC shared task,
Svitlana, Johannes and Maik
[1] Anantha, R., Vakulenko, S., Tu, Z., Longpre, S., Pulman, S., &
Chappidi, S. (2020). Open-Domain Question Answering Goes Conversational
via Question Rewriting. NAACL’21 (to appear)
https://arxiv.org/abs/2010.04898
[2] https://github.com/apple/ml-qrecc
[3] QReCC - Question Rewriting in Conversational Context (Version
2021-05-19) [Data set] https://zenodo.org/record/4772532#.YK48Fy0Rp0s
[4] SCAI: Search-Oriented Conversational AI Online Event 8 October 2021
https://scai.info
Answering Challenge***
We are pleased to announce that this year we will be hosting a shared
task on open-domain conversational question answering (QA) co-located
with SCAI 2021 (https://scai.info). The shared task aims to establish a
reliable benchmark for conversational QA and encourage collaboration
between communities working on dialogue response generation, passage
retrieval and reading comprehension.
Web page: https://scai.info/scai-qrecc
Leaderboard: https://www.tira.io/task/scai-qrecc
Registration: https://forms.gle/JFBXZXPtWPqbtLhu8
Register to receive further updates, make leaderboard submissions, get
access to the TIRA forum and keep in touch with other participating teams.
Submission deadline: September 8, 2021
Results announcement: September 30, 2021
Workshop presentations: October 8, 2021
* Task *
Conversational question answering (QA) is one of the core applications
for retrieval-based chatbots. In conversational QA, the task is to
answer a series of contextually-dependent questions like they may occur
in a natural human-to-human conversation. It is also possible to
participate with non-conversational approaches in the conversational
task by using our question rewrites. For more details on question
rewriting see [1].
* Dataset *
The challenge uses the QReCC dataset [1] for evaluation, to appear in
NAACL’21 proceedings. The dataset contains 14K conversations with 81K
question-answer pairs and 54M passages [2]. The passage collection was
constructed by processing 10M web pages from the Common Crawl and the
Wayback Machine [3]. We will use the submitted runs to pull alternative
answers and relevant passages that are discovered by the participating
systems to extend the coverage of the ground truth annotations and
improve the evaluation metrics.
* Evaluation *
The primary evaluation metrics is F1 and EM performance on the QA task.
However, we also, optionally, report MRR and ROUGE for passage retrieval
and question rewriting subtasks to provide better insights on the
performance over the intermediate steps.
* Workshop *
Participating teams will be invited to submit a short notebook paper
detailing their approach for publication in conjunction with the SCAI’21
workshop [4].
* Contact *
scai-qrecc@googlegroups.com
Kind regards,
Organisers of the SCAI QReCC shared task,
Svitlana, Johannes and Maik
[1] Anantha, R., Vakulenko, S., Tu, Z., Longpre, S., Pulman, S., &
Chappidi, S. (2020). Open-Domain Question Answering Goes Conversational
via Question Rewriting. NAACL’21 (to appear)
https://arxiv.org/abs/2010.04898
[2] https://github.com/apple/ml-qrecc
[3] QReCC - Question Rewriting in Conversational Context (Version
2021-05-19) [Data set] https://zenodo.org/record/4772532#.YK48Fy0Rp0s
[4] SCAI: Search-Oriented Conversational AI Online Event 8 October 2021
https://scai.info
اگر کسی از شما یا دوستان شما تخصص های فوق را دارند می توانند مستقیما در سایت جاب اینجا اپلای کنند. متشکرم
Forwarded from کانال اطلاعرسانی آزمایشگاه سپهر (Ali Reza Feizi Derakhshi)
#فراخوان_مقاله
Artificial Intelligence in Biomedical Big Data and Digital Healthcare
مجله:
Future Generation Computer Systems
موضوعات:
· Deep-learning-empowered artificial intelligence models for biomedical applications
· Biomedical knowledge reasoning
· Biomedical knowledge graph construction and completion
· Biomedical knowledge graph embedding
· Biomedical knowledge extraction from electronic medical record
· Explainable diagnostics support system
· Diagnostics support system based on electronic medical record
· Multi-modal biomedical data analysis models
· Multi-modal transformer models for biomedical data
· Data anonymization methods for biomedical data
· Privacy-aware biomedical data analysis
· Federated learning for biomedical data
· Causal Inference for multi-modal biomedical data
· Self-supervised learning for multi-modal biomedical data
· Biomedical image/signal processing
· Sensing, detection, and recognition in biomedical image/signal
· Natural language processing and knowledge discovery in biomedical documents
· Emerging digital healthcare applications
· Wearable medical wireless sensors
· Mobile and cloud computing for digital healthcare
· Security, trust, and privacy in digital healthcare
لینک فراخوان
لینک مجله
@cominsys_channel
Artificial Intelligence in Biomedical Big Data and Digital Healthcare
مجله:
Future Generation Computer Systems
موضوعات:
· Deep-learning-empowered artificial intelligence models for biomedical applications
· Biomedical knowledge reasoning
· Biomedical knowledge graph construction and completion
· Biomedical knowledge graph embedding
· Biomedical knowledge extraction from electronic medical record
· Explainable diagnostics support system
· Diagnostics support system based on electronic medical record
· Multi-modal biomedical data analysis models
· Multi-modal transformer models for biomedical data
· Data anonymization methods for biomedical data
· Privacy-aware biomedical data analysis
· Federated learning for biomedical data
· Causal Inference for multi-modal biomedical data
· Self-supervised learning for multi-modal biomedical data
· Biomedical image/signal processing
· Sensing, detection, and recognition in biomedical image/signal
· Natural language processing and knowledge discovery in biomedical documents
· Emerging digital healthcare applications
· Wearable medical wireless sensors
· Mobile and cloud computing for digital healthcare
· Security, trust, and privacy in digital healthcare
لینک فراخوان
لینک مجله
@cominsys_channel
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