🔵 Sensing Web Social Signals for #Cryptocurrencies #Data_Science & #Computational_Social_Science
#Travel_grant application for ETH CryptoDatathon
Are you a #geek in #data_science ( i.e. #data_mining, #machine_learning, #natural_language_processing, etc. ), #crypto_currency, or #complex_systems? Then, here is a perfect event for you, ETH CryptoDatathon, which stands for Crypto + Data + Hackathon at the main building of ETH Zurich.
The theme of this year is Sensing Web Social Signals for Cryptocurrencies. You are expected to make use of a variety of web data collection, data science, big data, NLP, and visualization techniques to dig into social media to explore its potential effect on the crypto-currency market.
In addition, during this six days' event, distinguished keynote speakers will deliver insights into various topics ranging from computational social science, crypto-currency, information retrieval, complex networks, social networks, and so on.
Now the registration is open. We welcome international participants to apply for the travel grant by simply registration. For selected applicants, we will cover accommodation in part.
For details, you could visit our website https://www.cryptodatathon.com/
For any questions, feel free to drop us a message at nino.antulov@gess.ethz.ch, and tian.guo@gess.ethz.ch
🔰 عزیزانی که علاقه مند هستند در این رویداد که در دانشگاه ETHZ سوئیس (که یکی از 10 دانشگاه برتر دنیا می باشد) شرکت کنند، با ما در ارتباط باشند:
🎭 Admin: @Dr_Apply
✔️ @ApplyTime
#Travel_grant application for ETH CryptoDatathon
Are you a #geek in #data_science ( i.e. #data_mining, #machine_learning, #natural_language_processing, etc. ), #crypto_currency, or #complex_systems? Then, here is a perfect event for you, ETH CryptoDatathon, which stands for Crypto + Data + Hackathon at the main building of ETH Zurich.
The theme of this year is Sensing Web Social Signals for Cryptocurrencies. You are expected to make use of a variety of web data collection, data science, big data, NLP, and visualization techniques to dig into social media to explore its potential effect on the crypto-currency market.
In addition, during this six days' event, distinguished keynote speakers will deliver insights into various topics ranging from computational social science, crypto-currency, information retrieval, complex networks, social networks, and so on.
Now the registration is open. We welcome international participants to apply for the travel grant by simply registration. For selected applicants, we will cover accommodation in part.
For details, you could visit our website https://www.cryptodatathon.com/
For any questions, feel free to drop us a message at nino.antulov@gess.ethz.ch, and tian.guo@gess.ethz.ch
🔰 عزیزانی که علاقه مند هستند در این رویداد که در دانشگاه ETHZ سوئیس (که یکی از 10 دانشگاه برتر دنیا می باشد) شرکت کنند، با ما در ارتباط باشند:
🎭 Admin: @Dr_Apply
✔️ @ApplyTime
Hello everyone,
Please consider submitting your paper to the 2nd Workshop on AI for Aging, Rehabilitation and Independent Assisted Living (ARIAL) held jointly in Stockholm with IJCAI'2018.
We will accept papers in two formats:
-Short papers - 4 pages (including references) .
-Extended Abstracts / Demo Papers - 2 pages (including references).
Deadline — 25th April'2018
More details about ARIAL and paper submission instructions - https://sites.google.com/view/arial2018/home
Accepted papers to ARIAL will be invited to submit an extended full length paper to the Journal of Healthcare Informatics Research (JHIR - Springer) and a fast track review will be conducted.
regards
✔️ @ApplyTime
Please consider submitting your paper to the 2nd Workshop on AI for Aging, Rehabilitation and Independent Assisted Living (ARIAL) held jointly in Stockholm with IJCAI'2018.
We will accept papers in two formats:
-Short papers - 4 pages (including references) .
-Extended Abstracts / Demo Papers - 2 pages (including references).
Deadline — 25th April'2018
More details about ARIAL and paper submission instructions - https://sites.google.com/view/arial2018/home
Accepted papers to ARIAL will be invited to submit an extended full length paper to the Journal of Healthcare Informatics Research (JHIR - Springer) and a fast track review will be conducted.
regards
✔️ @ApplyTime
Google
ARIAL@IJCAI18
C A L L F O R P A P E R S
DA2PL'2018: From Multiple Criteria Decision Aid to Preference Learning
Poznan University of Technology, Poznan, Poland
November 22-23, 2018
https://da2pl.cs.put.poznan.pl
The DA2PL workshop has been launched with the goal of bringing together researchers from operations research and the decision sciences with scholars from machine learning. It aims at providing a forum for discussing recent advances and identifying new research challenges in the intersection of both fields, which is marked by the growing field of preference learning, thereby supporting a cross-fertilization of these disciplines.
Following the three previous editions of this workshop, which took place in Mons in 2012, Paris in 2014 and Paderborn in 2016, DA2PL'2018 will be held at the Poznan University of Technology (Poznan, Poland).
DA2PL'2018 solicits contributions to the usage of theoretically supported preference models and formalisms in preference learning as well as communications devoted to innovative preference learning methods in decision analysis and multiple criteria decision aiding. Specific topics of interest include, but are not limited to
— quantitative and qualitative approaches to modeling preferences, user feedback and training data
— preference representation in terms of graphical models, logical formalisms, and soft constraints
— dealing with incomplete and uncertain preferences
— preference aggregation and disaggregation
— learning utility functions using regression-based approaches
— preference elicitation and active learning
— preference learning in combinatorial domains
— learning relational preference models and related regression problems
— classification problems, such as ordinal and hierarchical classification
— inducing monotonic decision models for preference representation
— comparison of different preference learning paradigms (e.g., monolithic vs. decomposition)
— ranking problems, such as object ranking, instance ranking and label ranking
— complementarity of preference models and hybrid methods
— explanation of recommendations
— applications of preference learning, such as web search, information retrieval, electronic commerce, games, personalization, recommender systems, etc.
Submissions
Submissions must be written in English and formatted according to the electronic template that is available on the conference website. The page limit is 8 for full papers, although extended abstracts (two pages as the maximum) are welcome, too. Submissions are managed through www.easychair.org. Each paper submitted to DA2PL will be reviewed by two referees.
We also provide an opportunity for doctoral students to explore and develop their research interests. A special session at the conference will be devoted for PhD students to present and discuss their ongoing research work. Therefore we encourage young researchers to submit their work also via submission site.
Important Dates
Paper submission deadline: September 1, 2018
Author notification: September 30, 2018
Camera-ready version: November 3, 2018
Conference: November 22-23 (Thursday,Friday), 2018
Organization and Contact
Conference Chairs: Krzysztof Dembczynski, Poznan University of Technology (krzysztof.dembczynski@cs.put.poznan.pl), Milosz Kadzinski, Poznan University of Technology (milosz.kadzinski@cs.put.poznan.pl)
Program Chairs: Eyke Hüllermeier, Paderborn University (eyke@upb.de), Vincent Mousseau, CentraleSupélec, Paris (vincent.mousseau@centralesupelec.fr)
✔️ @ApplyTime
DA2PL'2018: From Multiple Criteria Decision Aid to Preference Learning
Poznan University of Technology, Poznan, Poland
November 22-23, 2018
https://da2pl.cs.put.poznan.pl
The DA2PL workshop has been launched with the goal of bringing together researchers from operations research and the decision sciences with scholars from machine learning. It aims at providing a forum for discussing recent advances and identifying new research challenges in the intersection of both fields, which is marked by the growing field of preference learning, thereby supporting a cross-fertilization of these disciplines.
Following the three previous editions of this workshop, which took place in Mons in 2012, Paris in 2014 and Paderborn in 2016, DA2PL'2018 will be held at the Poznan University of Technology (Poznan, Poland).
DA2PL'2018 solicits contributions to the usage of theoretically supported preference models and formalisms in preference learning as well as communications devoted to innovative preference learning methods in decision analysis and multiple criteria decision aiding. Specific topics of interest include, but are not limited to
— quantitative and qualitative approaches to modeling preferences, user feedback and training data
— preference representation in terms of graphical models, logical formalisms, and soft constraints
— dealing with incomplete and uncertain preferences
— preference aggregation and disaggregation
— learning utility functions using regression-based approaches
— preference elicitation and active learning
— preference learning in combinatorial domains
— learning relational preference models and related regression problems
— classification problems, such as ordinal and hierarchical classification
— inducing monotonic decision models for preference representation
— comparison of different preference learning paradigms (e.g., monolithic vs. decomposition)
— ranking problems, such as object ranking, instance ranking and label ranking
— complementarity of preference models and hybrid methods
— explanation of recommendations
— applications of preference learning, such as web search, information retrieval, electronic commerce, games, personalization, recommender systems, etc.
Submissions
Submissions must be written in English and formatted according to the electronic template that is available on the conference website. The page limit is 8 for full papers, although extended abstracts (two pages as the maximum) are welcome, too. Submissions are managed through www.easychair.org. Each paper submitted to DA2PL will be reviewed by two referees.
We also provide an opportunity for doctoral students to explore and develop their research interests. A special session at the conference will be devoted for PhD students to present and discuss their ongoing research work. Therefore we encourage young researchers to submit their work also via submission site.
Important Dates
Paper submission deadline: September 1, 2018
Author notification: September 30, 2018
Camera-ready version: November 3, 2018
Conference: November 22-23 (Thursday,Friday), 2018
Organization and Contact
Conference Chairs: Krzysztof Dembczynski, Poznan University of Technology (krzysztof.dembczynski@cs.put.poznan.pl), Milosz Kadzinski, Poznan University of Technology (milosz.kadzinski@cs.put.poznan.pl)
Program Chairs: Eyke Hüllermeier, Paderborn University (eyke@upb.de), Vincent Mousseau, CentraleSupélec, Paris (vincent.mousseau@centralesupelec.fr)
✔️ @ApplyTime
Earth Day - together, worldwide for our planet.
Since 1970 people are celebrating on April 22nd worldwide in honor of the Planet!
✔️ @ApplyTime
Since 1970 people are celebrating on April 22nd worldwide in honor of the Planet!
✔️ @ApplyTime
Dear all,
We are looking for a motivated researcher to join, at a post-doctoral level, a project on the automatic analysis of legal agreements (Terms of Use, informed consent, privacy and cookie policies, etc), in the context of the GDPR. The project will be performed together with an international consortium including data projection agencies, law schools, and other technical academic and industrial players; with funding from the European Commission as part of the H2020 framework programme.
The selected candidate will perform her/his work inside the Natural Language Processing team, interacting with scientists from the team and beyond.
Requirements:
Ph.D. in natural language processing (NLP) or machine learning.
Knowledge of latest developments in statistical and deep learning for information extraction from text
Good publication record in top-tier NLP, information retrieval or machine learning conferences.
Strong development skills, preferably in Python and knowledge of deep learning frameworks
More information and application instructions here: http://www.europe.naverlabs.com/NAVER-LABS-Europe/Jobs/NLP-Researcher-Analysis-of-Legal-Agreements
—
Matthias Gallé
Senior Scientist and Group Lead (NLP)
Naver Labs Europe
✔️ @ApplyTime
We are looking for a motivated researcher to join, at a post-doctoral level, a project on the automatic analysis of legal agreements (Terms of Use, informed consent, privacy and cookie policies, etc), in the context of the GDPR. The project will be performed together with an international consortium including data projection agencies, law schools, and other technical academic and industrial players; with funding from the European Commission as part of the H2020 framework programme.
The selected candidate will perform her/his work inside the Natural Language Processing team, interacting with scientists from the team and beyond.
Requirements:
Ph.D. in natural language processing (NLP) or machine learning.
Knowledge of latest developments in statistical and deep learning for information extraction from text
Good publication record in top-tier NLP, information retrieval or machine learning conferences.
Strong development skills, preferably in Python and knowledge of deep learning frameworks
More information and application instructions here: http://www.europe.naverlabs.com/NAVER-LABS-Europe/Jobs/NLP-Researcher-Analysis-of-Legal-Agreements
—
Matthias Gallé
Senior Scientist and Group Lead (NLP)
Naver Labs Europe
✔️ @ApplyTime
Three-Year Postdoctoral Research Fellow position in Data Science available at UTS
https://www.seek.com.au/job/35898410?type=standard&userqueryid=90ab1a62a6e7461aef05cbf86d76b61f-3504617
Unit: Advanced Data Analytics, Faculty of Engineering and IT, UTS
Salary (Level B): $100,923 – $115,486 p.a. p.a. plus 17% super.
Work type: Full Time - Fixed Term (three years with possibility to be extended)
Location: Broadway Campus, UTS, Ultimo, NSW 2008
The Advanced Analytics Institute (AAi) at the University of Technology, Sydney, is seeking a postdoctoral research fellow to work in data science and data analytics research. AAi is a world-leading research organisation with a focus on big data, data sciences and data analytics for its high-quality Research, high calibre analyst Education, and high impact Development. Bringing together data analytics experts across multiple disciplines – engineering, information technology, health, science, business and law – AAi is internationally recognised as a leader in data mining, advanced analytics, bioinformatics and multimedia analytics. It delivers real-world solutions to contemporary big data questions and assists industry partners to use data as a tool for effective business decisions.
The role
The appointed Postdoctoral Research Fellow is to participate in research projects on data science, artificial intelligence, NLP, and recommender systems. S/he will contribute significantly to a range of academic duties including research and scholarship, team management, and HDR supervision. The Postdoctoral Fellow will support the development of high quality research funding applications and world-class research publications.
The person
The successful applicant should have a Ph.D. degree in a computer science, artificial intelligence or statistics or related areas with a strong background in data science, artificial intelligence, NLP, or recommender systems with substantial experience in algorithmic programming and computational model development, and industry project experience (plus). Strong publication track record is essential. Good communication skills are required.
Remuneration
The position is expected to be filled up immediately. It is a full-time three-year fixed term appointment (with possibility of extension subject to the performance and availability of future funding) at Academic Level B. The remuneration package will be:
Academic level B: $100,923 – $115,486 p.a., plus employer superannuation contributions of 17%.
Enquiries
Applications must be submitted online via UTS iRecruitment website https://recruitment.uts.edu.au/OA_HTML/OA.jsp?OAFunc=IRC_VIS_VAC_DISPLAY&p_svid=107681&p_spid=3238671, any enquires should go to Dr Guandong Xu, guandong.xu@uts.edu.au. Application closing date: 2 May 2018 at 11:59pm and successful appointee is expected to start the employment immediately.
✔️ @ApplyTime
https://www.seek.com.au/job/35898410?type=standard&userqueryid=90ab1a62a6e7461aef05cbf86d76b61f-3504617
Unit: Advanced Data Analytics, Faculty of Engineering and IT, UTS
Salary (Level B): $100,923 – $115,486 p.a. p.a. plus 17% super.
Work type: Full Time - Fixed Term (three years with possibility to be extended)
Location: Broadway Campus, UTS, Ultimo, NSW 2008
The Advanced Analytics Institute (AAi) at the University of Technology, Sydney, is seeking a postdoctoral research fellow to work in data science and data analytics research. AAi is a world-leading research organisation with a focus on big data, data sciences and data analytics for its high-quality Research, high calibre analyst Education, and high impact Development. Bringing together data analytics experts across multiple disciplines – engineering, information technology, health, science, business and law – AAi is internationally recognised as a leader in data mining, advanced analytics, bioinformatics and multimedia analytics. It delivers real-world solutions to contemporary big data questions and assists industry partners to use data as a tool for effective business decisions.
The role
The appointed Postdoctoral Research Fellow is to participate in research projects on data science, artificial intelligence, NLP, and recommender systems. S/he will contribute significantly to a range of academic duties including research and scholarship, team management, and HDR supervision. The Postdoctoral Fellow will support the development of high quality research funding applications and world-class research publications.
The person
The successful applicant should have a Ph.D. degree in a computer science, artificial intelligence or statistics or related areas with a strong background in data science, artificial intelligence, NLP, or recommender systems with substantial experience in algorithmic programming and computational model development, and industry project experience (plus). Strong publication track record is essential. Good communication skills are required.
Remuneration
The position is expected to be filled up immediately. It is a full-time three-year fixed term appointment (with possibility of extension subject to the performance and availability of future funding) at Academic Level B. The remuneration package will be:
Academic level B: $100,923 – $115,486 p.a., plus employer superannuation contributions of 17%.
Enquiries
Applications must be submitted online via UTS iRecruitment website https://recruitment.uts.edu.au/OA_HTML/OA.jsp?OAFunc=IRC_VIS_VAC_DISPLAY&p_svid=107681&p_spid=3238671, any enquires should go to Dr Guandong Xu, guandong.xu@uts.edu.au. Application closing date: 2 May 2018 at 11:59pm and successful appointee is expected to start the employment immediately.
✔️ @ApplyTime
* Extended deadline for early registration: May 20th, 2018 *
sfla2018.di.uniba.it
Call for Participation
The fourth edition of the European Summer School on Fuzzy Logic and Applications (SFLA2018) will take place between 25 and 29, June 2018, in Bari - Italy. The school is promoted by the European Society for Fuzzy Logic and Technology (EUSFLAT).
The School proposes several courses delivered by world-leading experts in the field. A key aspect of the School is the focus on communication and collaboration among participants and lecturers, ensuring time for discussions so that a fruitful ground for exchanging knowledge can be established. Students and young researchers attending the school will be given also the opportunity to provide short presentations of their activities.
Intended audience
PhD students and young researchers represent the ideal audience for the School which aims at introducing the core aspects and the recent developments of Fuzzy Logic and related applications.
Confirmed Speakers
Giovanna Castellano, University of Bari Aldo Moro, Italy
Sebatien Destercke, French National Center for Scientific Research - CNRS, France
Francesco Masulli, University of Genova, Italy
José María Alonso Moral, University of Santiago de Compostela, Spain
Gabriella Pasi, University of Milano Bicocca, Italy
Hugues Bersini, Université Libre de Bruxelles , Belgium
Mariagrazia Dotoli, Polytechnic university of Bari, Italy
Uzay Kaymak, University of Eindhoven
Settimo Termini, University of Palermo, Italy
Martin Štěpnička, University of Ostrava, Czech Republic
Pietro Ducange, eCampus University, Italy
Scientific Program Committee
José María Alonso Moral (University of Santiago de Compostela, Spain)
Giovanna Castellano (University of Bari Aldo Moro, Italy)
Ciro Castiello (University of Bari Aldo Moro, Italy)
Francesco Masulli (University of Genova, Italy)
Corrado Mencar (University of Bari Aldo Moro, Italy)
Gabriella Pasi (University of Milano Bicocca, Italy)
Martin Štěpnička (University of Ostrava, Czech Republic)
Organizing Committee
Corrado Mencar (General Chair)
Ciro Castiello (Financial Chair)
Giovanna Castellano (Local Arrangement Chair)
Gabriella Casalino (Publicity Chair)
Registration is open
Early registration fee (before May 20th, 2018): € 400 (VAT included).
For more information, please visit our website sfla2018.di.uniba.it
and feel free to contact the organizers: summerschool.sfla2018@uniba.it
Looking forward to welcome you in Bari.
The SFLA2018 Organizing Committee.
✔️ @ApplyTime
sfla2018.di.uniba.it
Call for Participation
The fourth edition of the European Summer School on Fuzzy Logic and Applications (SFLA2018) will take place between 25 and 29, June 2018, in Bari - Italy. The school is promoted by the European Society for Fuzzy Logic and Technology (EUSFLAT).
The School proposes several courses delivered by world-leading experts in the field. A key aspect of the School is the focus on communication and collaboration among participants and lecturers, ensuring time for discussions so that a fruitful ground for exchanging knowledge can be established. Students and young researchers attending the school will be given also the opportunity to provide short presentations of their activities.
Intended audience
PhD students and young researchers represent the ideal audience for the School which aims at introducing the core aspects and the recent developments of Fuzzy Logic and related applications.
Confirmed Speakers
Giovanna Castellano, University of Bari Aldo Moro, Italy
Sebatien Destercke, French National Center for Scientific Research - CNRS, France
Francesco Masulli, University of Genova, Italy
José María Alonso Moral, University of Santiago de Compostela, Spain
Gabriella Pasi, University of Milano Bicocca, Italy
Hugues Bersini, Université Libre de Bruxelles , Belgium
Mariagrazia Dotoli, Polytechnic university of Bari, Italy
Uzay Kaymak, University of Eindhoven
Settimo Termini, University of Palermo, Italy
Martin Štěpnička, University of Ostrava, Czech Republic
Pietro Ducange, eCampus University, Italy
Scientific Program Committee
José María Alonso Moral (University of Santiago de Compostela, Spain)
Giovanna Castellano (University of Bari Aldo Moro, Italy)
Ciro Castiello (University of Bari Aldo Moro, Italy)
Francesco Masulli (University of Genova, Italy)
Corrado Mencar (University of Bari Aldo Moro, Italy)
Gabriella Pasi (University of Milano Bicocca, Italy)
Martin Štěpnička (University of Ostrava, Czech Republic)
Organizing Committee
Corrado Mencar (General Chair)
Ciro Castiello (Financial Chair)
Giovanna Castellano (Local Arrangement Chair)
Gabriella Casalino (Publicity Chair)
Registration is open
Early registration fee (before May 20th, 2018): € 400 (VAT included).
For more information, please visit our website sfla2018.di.uniba.it
and feel free to contact the organizers: summerschool.sfla2018@uniba.it
Looking forward to welcome you in Bari.
The SFLA2018 Organizing Committee.
✔️ @ApplyTime
دوستان گرامی،
با توجه به سرنوشت مبهم تلگرام در ایران، لطفا با باز کردن لینک زیر در وبسایت اپلای تایم عضو شوید. در صورت بسته شدن کامل تلگرام، راه ارتباطی جدید را برای شما ارسال خواهیم کرد.
http://applytime.ir/register/
با احترام،
اپلای تایم
با توجه به سرنوشت مبهم تلگرام در ایران، لطفا با باز کردن لینک زیر در وبسایت اپلای تایم عضو شوید. در صورت بسته شدن کامل تلگرام، راه ارتباطی جدید را برای شما ارسال خواهیم کرد.
http://applytime.ir/register/
با احترام،
اپلای تایم
Applications are invited for a fully-funded 4-year PhD scholarship within the Computational Web Intelligence (CWI) lab. The research will be conducted in cooperation with the Laboratory of Intelligent Decision Support Systems (IDSS), an organizational unit within the Institute of Computing Science of the Poznań University of Technology.
The PhD scholarship involves the extension of the dominance based rough set approach (DRSA) by means of fuzzy logic, used at the stage of defining rough approximations. These fuzzy-rough approximations are then used in inductive learning of decision rules. The set of decision rules induced in this way is on one hand a preference model and on the other hand a basic classifier in an ensemble used for classification of unseen objects. It will build on the results of previous research conducted at CWI, IDSS and at the Department of Economics and Business of the University of Catania.
Your key responsibilities include:
* Designing new fuzzy rough set models of DRSA, and performing analysis of their theoretical properties;
* Designing new ML algorithms to test the proposed models;
* Setting up experimental studies with benchmark data to evaluate your algorithms;
* Working together with other PhD students and senior researchers involved in the project;
* Reporting and presenting your research in top-tier international journals and conferences;
* Successfully defending a doctoral dissertation at Ghent University, leading to a joint PhD degree in co-tutelle with Poznań University of Technology;
* Contributing (to a limited extent) to teaching and community engagement activities within the department.
We are especially interested in candidates with the following profile:
* A Masters' degree in Computer Science or Mathematics;
* Very good to excellent study grades, as evident from university trannoscripts;
* Excellent programming skills (e.g. Java, Python, ...);
* Good knowledge of machine learning, artificial intelligence and mathematical modeling;
* Knowledge of multi-criteria decision aiding methodologies is a plus;
* Strong motivation and aptitude to tackle challenging research problems and to complete the PhD within the prescribed period;
* Good interpersonal and team-playing skills;
* Proficiency in English and excellent writing skills;
* Preparedness to spend at least six months of the scholarship at Poznań University of Technology.
We offer:
* A four-year full-time (100%) PhD student position, leading to a joint doctoral degree awarded by Ghent University and Poznań University of Technology;
* A competitive salary as set out by the Flemish Government;
* A dynamic, multi-disciplinary and ambitious research team with a wide international network (Ghent University, University of Poznań, University of Catania);
* Expertise, state-of-the-art research infrastructure;
* A four-year Doctoral Training Program at Ghent University.
More information can be found at:
http://www.cwi.ugent.be/vacancies.html
✔ @ApplyTime
The PhD scholarship involves the extension of the dominance based rough set approach (DRSA) by means of fuzzy logic, used at the stage of defining rough approximations. These fuzzy-rough approximations are then used in inductive learning of decision rules. The set of decision rules induced in this way is on one hand a preference model and on the other hand a basic classifier in an ensemble used for classification of unseen objects. It will build on the results of previous research conducted at CWI, IDSS and at the Department of Economics and Business of the University of Catania.
Your key responsibilities include:
* Designing new fuzzy rough set models of DRSA, and performing analysis of their theoretical properties;
* Designing new ML algorithms to test the proposed models;
* Setting up experimental studies with benchmark data to evaluate your algorithms;
* Working together with other PhD students and senior researchers involved in the project;
* Reporting and presenting your research in top-tier international journals and conferences;
* Successfully defending a doctoral dissertation at Ghent University, leading to a joint PhD degree in co-tutelle with Poznań University of Technology;
* Contributing (to a limited extent) to teaching and community engagement activities within the department.
We are especially interested in candidates with the following profile:
* A Masters' degree in Computer Science or Mathematics;
* Very good to excellent study grades, as evident from university trannoscripts;
* Excellent programming skills (e.g. Java, Python, ...);
* Good knowledge of machine learning, artificial intelligence and mathematical modeling;
* Knowledge of multi-criteria decision aiding methodologies is a plus;
* Strong motivation and aptitude to tackle challenging research problems and to complete the PhD within the prescribed period;
* Good interpersonal and team-playing skills;
* Proficiency in English and excellent writing skills;
* Preparedness to spend at least six months of the scholarship at Poznań University of Technology.
We offer:
* A four-year full-time (100%) PhD student position, leading to a joint doctoral degree awarded by Ghent University and Poznań University of Technology;
* A competitive salary as set out by the Flemish Government;
* A dynamic, multi-disciplinary and ambitious research team with a wide international network (Ghent University, University of Poznań, University of Catania);
* Expertise, state-of-the-art research infrastructure;
* A four-year Doctoral Training Program at Ghent University.
More information can be found at:
http://www.cwi.ugent.be/vacancies.html
✔ @ApplyTime
All applicants with user interface / machine learning experience welcome. Official posting below.
- Mark
===
Machine Learning Postdoctoral Position at U. of Toronto (Interactive Media Lab in Industrial Engineering)
We are seeking a postdoctoral candidate who holds a PhD in engineering or computer science, to work in the area of innovative user interfaces between humans and smart agents. Experience in machine learning, mixed integer linear programming optimization, deep learning, Bayesian networks, data mining, or a related data-processing field is required. Strong programming skills are required. Familiarity with Android operating system is preferred
Experience with human factors and user interface design is an asset. The main role of the candidate will be to collaborate with an industry partner and the university research team members on the development of novel user interfaces for an intelligent smart phone assistant. An additional role is to provide strong leadership to MASc and PhD students in the team.
Excellent communication skills, strong independent research skills, and sensitivity to industry partner direction are required. The candidate will be expected to work independently, provide leadership to an interdisciplinary team of graduate students, produce publishable results, and publish frequently.
Initial funding for 1 year is available. An extension of funding to 2 years is possible, depending on project success and availability of funds.
The application package (to be emailed to Prof. M. Chignell) should include a cover letter and CV, including a list of 3 professional references.
**Deadline: May 3, 2018
Dr. Mark Chignell
Professor, Industrial Engineering and Computer Science
Department of Mechanical & Industrial Engineering
Faculty of Applied Science & Engineering
University of Toronto
5 King's College Road
Toronto, ON Canada M5S 3G8
Phone: +1 (416) 978-8951
(No Voicemail, send messages by email)
Fax: +1 (416) 978-7753
Email: chignell(at)mie(dot)utoronto(dot)ca
Web: https://www.mie.utoronto.ca/mie/faculty/chignell
https://imedia.mie.utoronto.ca/
✔ @ApplyTime
- Mark
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Machine Learning Postdoctoral Position at U. of Toronto (Interactive Media Lab in Industrial Engineering)
We are seeking a postdoctoral candidate who holds a PhD in engineering or computer science, to work in the area of innovative user interfaces between humans and smart agents. Experience in machine learning, mixed integer linear programming optimization, deep learning, Bayesian networks, data mining, or a related data-processing field is required. Strong programming skills are required. Familiarity with Android operating system is preferred
Experience with human factors and user interface design is an asset. The main role of the candidate will be to collaborate with an industry partner and the university research team members on the development of novel user interfaces for an intelligent smart phone assistant. An additional role is to provide strong leadership to MASc and PhD students in the team.
Excellent communication skills, strong independent research skills, and sensitivity to industry partner direction are required. The candidate will be expected to work independently, provide leadership to an interdisciplinary team of graduate students, produce publishable results, and publish frequently.
Initial funding for 1 year is available. An extension of funding to 2 years is possible, depending on project success and availability of funds.
The application package (to be emailed to Prof. M. Chignell) should include a cover letter and CV, including a list of 3 professional references.
**Deadline: May 3, 2018
Dr. Mark Chignell
Professor, Industrial Engineering and Computer Science
Department of Mechanical & Industrial Engineering
Faculty of Applied Science & Engineering
University of Toronto
5 King's College Road
Toronto, ON Canada M5S 3G8
Phone: +1 (416) 978-8951
(No Voicemail, send messages by email)
Fax: +1 (416) 978-7753
Email: chignell(at)mie(dot)utoronto(dot)ca
Web: https://www.mie.utoronto.ca/mie/faculty/chignell
https://imedia.mie.utoronto.ca/
✔ @ApplyTime