Postdoctoral Research Associate in Machine Learning for Water Resources Modelling
Dear Friends,
The School of Biomedical Engineering and School of Computer Science in the Faculty of Engineering at The University of Sydney has recently established new research areas in water quality modelling and sensing; water safety and treatment; data science, artificial intelligence or machine learning methods to predict and understand water quality parameters. The Faculty of Engineering has also set up the Digital Sciences Initiative (DSI) to undertake research in both fundamental digital sciences and applied digital technologies. Part of the DSI effort is to drive the Water Resources Data Science for Water Safety in the Faculty of Engineering, a joint effort led by the School of Biomedical Engineering in collaboration with the School of Computer Science, and the School of Electrical Engineering.
We are currently seeking to appoint one Postdoctoral Research Associate to work on areas such as computational data science, machine learning, and artificial intelligence in water quality prediction and investigation. The successful applicant will also be part of the Sydney Nano, which is a large and diverse Nano-Institute with research strengths in many areas. In addition, we have a strong applied water sensing group working on various aspects of water science research.
Link to apply:
https://usyd.wd3.myworkdayjobs.com/USYD_EXTERNAL_CAREER_SITE/job/Camperdown-Campus/Postdoctoral-Research-Associate-in-Computer-Science-and-Biomedical-Engineering_0094047-1
Thank you!✔️ @ApplyTime
Dear Friends,
The School of Biomedical Engineering and School of Computer Science in the Faculty of Engineering at The University of Sydney has recently established new research areas in water quality modelling and sensing; water safety and treatment; data science, artificial intelligence or machine learning methods to predict and understand water quality parameters. The Faculty of Engineering has also set up the Digital Sciences Initiative (DSI) to undertake research in both fundamental digital sciences and applied digital technologies. Part of the DSI effort is to drive the Water Resources Data Science for Water Safety in the Faculty of Engineering, a joint effort led by the School of Biomedical Engineering in collaboration with the School of Computer Science, and the School of Electrical Engineering.
We are currently seeking to appoint one Postdoctoral Research Associate to work on areas such as computational data science, machine learning, and artificial intelligence in water quality prediction and investigation. The successful applicant will also be part of the Sydney Nano, which is a large and diverse Nano-Institute with research strengths in many areas. In addition, we have a strong applied water sensing group working on various aspects of water science research.
Link to apply:
https://usyd.wd3.myworkdayjobs.com/USYD_EXTERNAL_CAREER_SITE/job/Camperdown-Campus/Postdoctoral-Research-Associate-in-Computer-Science-and-Biomedical-Engineering_0094047-1
Thank you!✔️ @ApplyTime
Postdoctoral position at DICE, Paderborn Univeristy - Germany
Paderborn University is a high-performance and internationally oriented university with approximately 20,000 students. Within interdisciplinary teams, we undertake forward-looking research, design innovative teaching concepts, and actively transfer knowledge into society. As an important research and cooperation partner, the university also shapes regional development strategies. We offer our more than 2,500 employees in research, teaching, technology, and administration a lively, family-friendly, equal opportunity environment, a lean management structure, and diverse opportunities. Join us to invent the future!
In the Faculty of Electrical Engineering, Computer Science, and Mathematics, the Department of Data Science offers a full-time position for postdoctoral researchers in the NLP group.
The NLP group works on the intersection of Data Science and Natural Language Processing areas. We focus on creating algorithms that allow computers to extract automatically large-scale knowledge from unstructured data and process them while preserving their semantic key information. We aim to make the acquired knowledge accessible and understandable for both humans and computers. Our team has started addressing two of the most important tasks in NLP by relying on Knowledge Graphs, Named Entity Recognition, and Entity Linking. Our research resulted in two state-of-the-art frameworks in respect of multilingualism and knowledge-graph-based algorithms. Recently, we expanded our focus on different NLP tasks ranging from basic research in computational linguistics to Question Answering, Machine Translation, Natural Language Generation, and Understanding.
For more information, please access the link below:
https://www.uni-paderborn.de/fileadmin/zv/4-4/stellenangebote/Kennziffer5342-5344_Englisch.pdf
PS: We extended the applications for two more weeks.
--
Dr. Diego Moussallem
Postdoctoral researcher
Ph.D. Computer Science and Mathematics - Paderborn University
M.Sc. Computer Science - Military Institute of Engineering
mobile: +49 0178 4599044
Skype diegomoussallem✔️ @ApplyTime
Paderborn University is a high-performance and internationally oriented university with approximately 20,000 students. Within interdisciplinary teams, we undertake forward-looking research, design innovative teaching concepts, and actively transfer knowledge into society. As an important research and cooperation partner, the university also shapes regional development strategies. We offer our more than 2,500 employees in research, teaching, technology, and administration a lively, family-friendly, equal opportunity environment, a lean management structure, and diverse opportunities. Join us to invent the future!
In the Faculty of Electrical Engineering, Computer Science, and Mathematics, the Department of Data Science offers a full-time position for postdoctoral researchers in the NLP group.
The NLP group works on the intersection of Data Science and Natural Language Processing areas. We focus on creating algorithms that allow computers to extract automatically large-scale knowledge from unstructured data and process them while preserving their semantic key information. We aim to make the acquired knowledge accessible and understandable for both humans and computers. Our team has started addressing two of the most important tasks in NLP by relying on Knowledge Graphs, Named Entity Recognition, and Entity Linking. Our research resulted in two state-of-the-art frameworks in respect of multilingualism and knowledge-graph-based algorithms. Recently, we expanded our focus on different NLP tasks ranging from basic research in computational linguistics to Question Answering, Machine Translation, Natural Language Generation, and Understanding.
For more information, please access the link below:
https://www.uni-paderborn.de/fileadmin/zv/4-4/stellenangebote/Kennziffer5342-5344_Englisch.pdf
PS: We extended the applications for two more weeks.
--
Dr. Diego Moussallem
Postdoctoral researcher
Ph.D. Computer Science and Mathematics - Paderborn University
M.Sc. Computer Science - Military Institute of Engineering
mobile: +49 0178 4599044
Skype diegomoussallem✔️ @ApplyTime
Doctoral scholarship holder radiotheranostics for personalized cancer treatment, University of Antwerp, Belgium
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PhD position: Ultra-fast thermometry on molecular heat engines at cryogenic temperatures, Université catholique de Louvain, Belgium
PhD Research Position INSPEXT “In-Situ Pellicle Exposure and Transmission ”, University of Twente, Netherlands
Doctoral position: FishPath - Turbulent eddies to create paths for safe downstream migration for salmonids and eel past hydropower intakes, ETH Zurich, Switzerland
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PhD student in Methods and Applications for Inertial Measurement Units | Embedded Systems, Signal Processing, Human-Computer Interaction, ETH Zurich, Switzerland
Post-doc in the project funded by the National Science Center in the Institute of Human Nutrition Sciences, Warsaw University of Life Sciences, Poland
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PhD Research Position INSPEXT “In-Situ Pellicle Exposure and Transmission ”, University of Twente, Netherlands
Doctoral position: FishPath - Turbulent eddies to create paths for safe downstream migration for salmonids and eel past hydropower intakes, ETH Zurich, Switzerland
Image analyst, ETH Zurich, Switzerland
PhD student in Methods and Applications for Inertial Measurement Units | Embedded Systems, Signal Processing, Human-Computer Interaction, ETH Zurich, Switzerland
Post-doc in the project funded by the National Science Center in the Institute of Human Nutrition Sciences, Warsaw University of Life Sciences, Poland
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Coordinator Marine Training and Education Unit of Ghent University (24114) - Biology, Ghent University, Belgium
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NCS2030 - PhD Fellowship in Debiasing of Probabilistic Forecasts, University of Stavanger, Norway
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Assistant (24429) - Morphology, Imaging, Orthopedics, Rehabilitation and Nutrition, Ghent University, Belgium
Post-doctoral assistant (23909) - Virology, parasitology and immunology, Ghent University, Belgium
Research manager virology for the KU Leuven VirusBank, KU Leuven, Belgium
PhD on integrated data and knowledge driven modeling of high-dimensional data, Eindhoven University of Technology, Netherlands
Postdoc position in Immunology, Institute Necker Enfants Malades (INEM), France
NCS2030 - PhD Fellowship in Reservoir Engineering/Physical Chemistry, University of Stavanger, Norway
NCS2030 - PhD Fellowship in Subsurface Geosciences, University of Stavanger, Norway
NCS2030 - PhD Fellowship in Robust reservoir management for safe and efficient CO2/H2 utilization and storage, University of Stavanger, Norway
NCS2030 - PhD Fellowship in Debiasing of Probabilistic Forecasts, University of Stavanger, Norway
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NCS2030 - PhD Fellowship in Reservoir Engineering/Physical Chemistry, University of Stavanger, Norway
PhD candidate | unravelling the role of soil microbial diversity in the soil carbon dynamics, Leiden University, Netherlands
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Postdoctoral position in the Ocean Infrastructure Group, Department of Political Science, University of Copenhagen, University of Copenhagen, Denmark
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PhD candidate | unravelling the role of soil microbial diversity in the soil carbon dynamics, Leiden University, Netherlands
Post-doctoral researcher, social media analytics for algorithmic profiling, Leiden University, Netherlands
PhD Researcher or Postdoc on Environmental impact assessment of green hydrogen and circular bio-coal from biowaste for steel manufacturing at the Industrial Ecology Department, Leiden University, Netherlands
Two Post-Doctoral Researchers in Comparative Political Economy on Labour Market and Welfare State Transformations as part of a new Horizon Europe project (4 years)., Leiden University, Netherlands
Five two-year post-doctoral research positions, Leiden University, Netherlands
Postdoctoral researcher in Public Health (0.8 FTE), Leiden University, Netherlands
THREE POSTDOCS ON VOLUMETRIC VIDEO FOR XR-BASED COMMUNICATION AND COLLABORATION, Centrum Wiskunde & Informatica (CWI), Netherlands
POSTDOC ON USER EXPERIENCE DESIGNER AND EVALUATION: INTERACTIVE XR APPLICATIONS, Centrum Wiskunde & Informatica (CWI), Netherlands
Postdoctoral position in the Ocean Infrastructure Group, Department of Political Science, University of Copenhagen, University of Copenhagen, Denmark
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Postdoctoral Researcher in the Philosophy, Theology or Religious Studies, Radboud University, Netherlands
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PhD Candidate: Rebel-to-State Transition in Civil War, Radboud University, Netherlands
Postdoctoral Researcher in Modelling and Control of Neural Systems at the Donders Center for Cognition, Radboud University, Netherlands
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Post-doc position (m/f/div) in magnonics (physics), Martin-Luther-Universität Halle-Wittenberg, Germany
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1 PostDoc (m/f/d), German Institute of Human Nutrition (DIfE), Germany
Modelling and control for MMC-based VSC HVDC system stability studies, KU Leuven, Belgium
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Postdoctoral Fellow - Computational Approaches focused on the Lung Microbiome, Wellcome Sanger Institute, UnitedKingdom
University Assistant (Doctoral Candidate) in the COSINUS dark matter experiment, TU Wien, Austria
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University Assistant (Prae-Doc) - Institute of Analysis and Scientific Computing, TU Wien, Austria
Head of Research Programme (f/m/d) Plasma Surface Modification, Leibniz Institute for Plasma Science and Technology (INP), Germany
Project Officer, University of Luxembourg, Luxembourg
Doctoral researcher in Psychology (DE / EN), University of Luxembourg, Luxembourg
1 PostDoc (m/f/d), German Institute of Human Nutrition (DIfE), Germany
Modelling and control for MMC-based VSC HVDC system stability studies, KU Leuven, Belgium
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Doctoral and Postdoctoral Positions, RWTH Aachen University, Germany
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Research Associate/Fellow in Microwave Processing (Fixed term), University of Nottingham, UnitedKingdom
Research Associate/Fellow (fixed term), University of Nottingham, UnitedKingdom
Research Associate/Fellow (Fixed term), University of Nottingham, UnitedKingdom
Research Associate/Fellow/Senior Research Fellow (Fixed term), University of Nottingham, UnitedKingdom
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Doctoral Student, University of Basel, Switzerland
Junior researcher ‘Online first aid for grief in Ukrainian refugees’, University of Twente, Netherlands
PhD position: Coastal Vulnerability (CVI) assessment for present and future, University of Twente, Netherlands
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The research group Data Mining and Machine Learning at the University of Vienna,
in a continued collaboration with the Volkswagen Natural Language Processing
Expert Center in Munich, is looking for graduates or advanced MSc students in
Computer Science, Computational Linguistics, Statistics, or related fields, that
are interested in doing a PhD in Machine Learning and Natural Language Processing.
The PhD candidate would be expected to be located in Munich for the duration of
the doctoral project. Please contact Prof. Benjamin Roth, Univ. of Vienna,
(benjamin.roth@univie.ac.at, use subject "ml nlp phd", please include a short CV)
to learn more about this opportunity.
--
Univ.-Prof. Dr. Benjamin Roth
Digitale Textwissenschaften
Universität Wien
Kolingasse 14
Raum 5.17
1090 Wien
email: benjamin.roth@univie.ac.at
✔️ @ApplyTime
in a continued collaboration with the Volkswagen Natural Language Processing
Expert Center in Munich, is looking for graduates or advanced MSc students in
Computer Science, Computational Linguistics, Statistics, or related fields, that
are interested in doing a PhD in Machine Learning and Natural Language Processing.
The PhD candidate would be expected to be located in Munich for the duration of
the doctoral project. Please contact Prof. Benjamin Roth, Univ. of Vienna,
(benjamin.roth@univie.ac.at, use subject "ml nlp phd", please include a short CV)
to learn more about this opportunity.
--
Univ.-Prof. Dr. Benjamin Roth
Digitale Textwissenschaften
Universität Wien
Kolingasse 14
Raum 5.17
1090 Wien
email: benjamin.roth@univie.ac.at
✔️ @ApplyTime
A fully-funded Industrial PhD position is available at the Department of Information Engineering and Computer Science of the University of Trento (DISI) and the Advanced Laboratory on Embedded Systems SRL (ALES), both in Trento, Italy, to conduct cutting edge research and innovation activity on the following topic:
Validation and Verification of Machine Learning Models
The candidate will investigate the applicability of advanced hybrid probabilistic inference techniques to the problem of probabilistic formal verification of ML models. S/he will study how Weighted Model Integration strategies can be improved to deal with the task, particularly in terms of scalability and approximations with guarantees, and develop a prototypical probabilistic formal verification tool for a use case in industrial avionics.
To apply to the call it is mandatory to have achieved a master degree by the end of October 2022, and to possess demonstrated English skills (e.g., via a master degree in English or via certificates such as TOEFL).
The position starts on November 1st, 2022 (or shortly after upon request).
Required skills:
- M.Sc. degree in computer science, mathematics, physics or related fields
- Basic knowledge of machine learning and artificial intelligence
- Excellent English skills (read, written, and spoken)
- Strong self-motivation and independence
Preferred skills:
- Expertise in automated reasoning and formal verification
Scientific supervisors: Andrea Passerini, Marco Roveri, Roberto Sebastiani
Industrial supervisors: Orlando Ferrante, Luigi Di Guglielmo
Main place of work: DISI and ALES.
DISI: The Department of Information Engineering and Computer Science ranked first among computer science departments in Italy and 78th worldwide according to the latest U.S. News Best Global Universities ranking. DISI has a strong focus on AI research, with top researchers and labs in computer vision, machine learning, natural language processing, speech recognition, intelligent optimization, knowledge representation and automated reasoning.
ALES: The Advanced Laboratory on Embedded Systems (ALES) SRL is a company of Collins Aerospace (https://www.collinsaerospace.com/), specialized in model-based technologies and methodologies for the design and verification of distributed safety-critical embedded systems.
Period abroad: A 6 month research period at the University of Aalborg is planned, to conduct research activity on theoretical aspects of probabilistic formal verification of machine learning models and potential applications in the automotive industry, under the supervision of Prof. Manfred Jaeger and Prof. Kim Larsen.
Doctoral program in Industrial Innovation: The Doctorate Program in Industrial Innovation is an interdisciplinary program co-founded by the University of Trento and the Fondazione Bruno Kessler. Companies are the key players of the Program that propose specific research problems (e.g. research topics) to solve and participate in the design of individual educational paths. Further information can be found at the program website.
Funding: The position is co-funded by the Italian National Recovery and Resilience Plan (NRRP) and ALES SRL. Further information on the NRRP industrial doctoral positions can be found here.
Application deadline: August 23, 2022 – 04:00 PM (Italian time, GMT +2).
HOW TO APPLY: Please apply here.
[choose "Doctoral Programme in Industrial Innovation 38th cycle" and look for a project noscriptd "Validation and Verification of Machine Learning Models"]
Feel free to contact the scientific and/or industrial supervisors for further information.
Best Regards
Andrea Passerini
----------------------------------------------------------------------------------
Andrea Passerini
Department of Information Engineering and Computer Science
University of Trento
Via Sommarive 5
38123, Povo di Trento - Italy
http://www.disi.unitn.it/~passerini
Phone: +39 0461 28 5224
email: andrea.passerini@unitn.it
✔️ @ApplyTime
Validation and Verification of Machine Learning Models
The candidate will investigate the applicability of advanced hybrid probabilistic inference techniques to the problem of probabilistic formal verification of ML models. S/he will study how Weighted Model Integration strategies can be improved to deal with the task, particularly in terms of scalability and approximations with guarantees, and develop a prototypical probabilistic formal verification tool for a use case in industrial avionics.
To apply to the call it is mandatory to have achieved a master degree by the end of October 2022, and to possess demonstrated English skills (e.g., via a master degree in English or via certificates such as TOEFL).
The position starts on November 1st, 2022 (or shortly after upon request).
Required skills:
- M.Sc. degree in computer science, mathematics, physics or related fields
- Basic knowledge of machine learning and artificial intelligence
- Excellent English skills (read, written, and spoken)
- Strong self-motivation and independence
Preferred skills:
- Expertise in automated reasoning and formal verification
Scientific supervisors: Andrea Passerini, Marco Roveri, Roberto Sebastiani
Industrial supervisors: Orlando Ferrante, Luigi Di Guglielmo
Main place of work: DISI and ALES.
DISI: The Department of Information Engineering and Computer Science ranked first among computer science departments in Italy and 78th worldwide according to the latest U.S. News Best Global Universities ranking. DISI has a strong focus on AI research, with top researchers and labs in computer vision, machine learning, natural language processing, speech recognition, intelligent optimization, knowledge representation and automated reasoning.
ALES: The Advanced Laboratory on Embedded Systems (ALES) SRL is a company of Collins Aerospace (https://www.collinsaerospace.com/), specialized in model-based technologies and methodologies for the design and verification of distributed safety-critical embedded systems.
Period abroad: A 6 month research period at the University of Aalborg is planned, to conduct research activity on theoretical aspects of probabilistic formal verification of machine learning models and potential applications in the automotive industry, under the supervision of Prof. Manfred Jaeger and Prof. Kim Larsen.
Doctoral program in Industrial Innovation: The Doctorate Program in Industrial Innovation is an interdisciplinary program co-founded by the University of Trento and the Fondazione Bruno Kessler. Companies are the key players of the Program that propose specific research problems (e.g. research topics) to solve and participate in the design of individual educational paths. Further information can be found at the program website.
Funding: The position is co-funded by the Italian National Recovery and Resilience Plan (NRRP) and ALES SRL. Further information on the NRRP industrial doctoral positions can be found here.
Application deadline: August 23, 2022 – 04:00 PM (Italian time, GMT +2).
HOW TO APPLY: Please apply here.
[choose "Doctoral Programme in Industrial Innovation 38th cycle" and look for a project noscriptd "Validation and Verification of Machine Learning Models"]
Feel free to contact the scientific and/or industrial supervisors for further information.
Best Regards
Andrea Passerini
----------------------------------------------------------------------------------
Andrea Passerini
Department of Information Engineering and Computer Science
University of Trento
Via Sommarive 5
38123, Povo di Trento - Italy
http://www.disi.unitn.it/~passerini
Phone: +39 0461 28 5224
email: andrea.passerini@unitn.it
✔️ @ApplyTime
PhD position on Fair and Inclusive Self-Supervised Learning for Speech Technologies (Paris/Grenoble)
The ANR project E-SSL (Efficient Self-Supervised Learning for
Inclusive and Innovative Speech Technologies) will start on November
1st. Self-supervised learning (SSL) has recently emerged as one of the
most promising artificial intelligence (AI) methods as it becomes now
feasible to take advantage of the colossal amounts of existing
unlabeled data to significantly improve the results of
various systems.
Speech technologies are widely used in our daily life and are
expanding the scope of our action, with decision-making systems,
including in critical areas such as health or legal aspects. In these
societal applications, the question of the use of these tools raises
the issue of the possible discrimination of people according to
criteria for which society requires equal treatment, such as gender,
origin, religion or disability... Recently, the machine learning
community has been confronted with the need to work on the possible
biases of algorithms, and many works have shown that the search for
the best performance is not the only goal to pursue [1]. For instance,
recent evaluations of ASR systems have shown that performances can
vary according to the gender but these variations depend both on data
used for learning and on models [2]. Therefore such systems are
increasingly scrutinized for being biased while trustworthy speech
technologies definitely represents a crucial expectation.
Both the question of bias and the concept of fairness have now become
important aspects of AI, and we now have to find the right threshold
between accuracy and the measure of fairness. Unfortunately, these
notions of fairness and bias are challenging to define and
theirmeanings can greatly differ [3].
The goals of this PhD position are threefold:
- First make a survey on the many definitions of robustness, fairness
and bias with the aim of coming up with definitions and metrics fit
for speech SSL models
- Then gather speech datasets with high amount of well-described
metadata
- Setup an evaluation protocol for SSL models and analyzing the
results. The PhD position will be co-supervised by Alexandre Allauzen
(Dauphine Université PSL, Paris) and Solange Rossato and François
Portet (Université Grenoble Alpes). Joint meetings are planned on a
regular basis and the student is expected to spend time in both
places. Moreover, two other PhD positions are open in this
project. The students, along with the partners will closely
collaborate. For instance, specific SSL models along with evaluation
criteria will be developed by the other PhD students.
Skills
- Master 2 in Natural Language Processing, Speech Processing, computer
science or data science.
- Good mastering of Python programming and deep learning framework.
- Previous experience in Self-Supervised Learning, acoustic modeling
or ASR would be a plus
- Very good communication skills in English
- Good command of French would be a plus but is not mandatory
To apply, send a CV and a cover letter to A. Allauzen before September
the 12th
[1] Mengesha, Z., Heldreth, C., Lahav, M., Sublewski, J. & Tuennerman,
E. “I don’t Think These Devices are Very Culturally Sensitive.”—Impact
of Automated Speech Recognition Errors on African Americans. Frontiers
in Artificial Intelligence 4. issn:
2624-8212. https://www.frontiersin.org/article/10.3389/frai.2021.725911(2021).
[2] Garnerin, M., Rossato, S. & Besacier, L. Investigating the Impact
of Gender Representation in ASR Training Data: a Case Study on
Librispeech in Proceedings of the 3rd Workshop on Gender Bias in
Natural Language Processing (2021), 86–92.[3] Mehrabi, N., Morstatter,
F., Saxena, N., Lerman, K. & Galstyan, A. A Survey on Bias and
Fairness in Machine Learning. ACMComput. Surv. 54. issn:
0360-0300. https://doi.org/10.1145/3457607 (July 2021).
--
Alexandre Allauzen
✔️ @ApplyTime
The ANR project E-SSL (Efficient Self-Supervised Learning for
Inclusive and Innovative Speech Technologies) will start on November
1st. Self-supervised learning (SSL) has recently emerged as one of the
most promising artificial intelligence (AI) methods as it becomes now
feasible to take advantage of the colossal amounts of existing
unlabeled data to significantly improve the results of
various systems.
Speech technologies are widely used in our daily life and are
expanding the scope of our action, with decision-making systems,
including in critical areas such as health or legal aspects. In these
societal applications, the question of the use of these tools raises
the issue of the possible discrimination of people according to
criteria for which society requires equal treatment, such as gender,
origin, religion or disability... Recently, the machine learning
community has been confronted with the need to work on the possible
biases of algorithms, and many works have shown that the search for
the best performance is not the only goal to pursue [1]. For instance,
recent evaluations of ASR systems have shown that performances can
vary according to the gender but these variations depend both on data
used for learning and on models [2]. Therefore such systems are
increasingly scrutinized for being biased while trustworthy speech
technologies definitely represents a crucial expectation.
Both the question of bias and the concept of fairness have now become
important aspects of AI, and we now have to find the right threshold
between accuracy and the measure of fairness. Unfortunately, these
notions of fairness and bias are challenging to define and
theirmeanings can greatly differ [3].
The goals of this PhD position are threefold:
- First make a survey on the many definitions of robustness, fairness
and bias with the aim of coming up with definitions and metrics fit
for speech SSL models
- Then gather speech datasets with high amount of well-described
metadata
- Setup an evaluation protocol for SSL models and analyzing the
results. The PhD position will be co-supervised by Alexandre Allauzen
(Dauphine Université PSL, Paris) and Solange Rossato and François
Portet (Université Grenoble Alpes). Joint meetings are planned on a
regular basis and the student is expected to spend time in both
places. Moreover, two other PhD positions are open in this
project. The students, along with the partners will closely
collaborate. For instance, specific SSL models along with evaluation
criteria will be developed by the other PhD students.
Skills
- Master 2 in Natural Language Processing, Speech Processing, computer
science or data science.
- Good mastering of Python programming and deep learning framework.
- Previous experience in Self-Supervised Learning, acoustic modeling
or ASR would be a plus
- Very good communication skills in English
- Good command of French would be a plus but is not mandatory
To apply, send a CV and a cover letter to A. Allauzen before September
the 12th
[1] Mengesha, Z., Heldreth, C., Lahav, M., Sublewski, J. & Tuennerman,
E. “I don’t Think These Devices are Very Culturally Sensitive.”—Impact
of Automated Speech Recognition Errors on African Americans. Frontiers
in Artificial Intelligence 4. issn:
2624-8212. https://www.frontiersin.org/article/10.3389/frai.2021.725911(2021).
[2] Garnerin, M., Rossato, S. & Besacier, L. Investigating the Impact
of Gender Representation in ASR Training Data: a Case Study on
Librispeech in Proceedings of the 3rd Workshop on Gender Bias in
Natural Language Processing (2021), 86–92.[3] Mehrabi, N., Morstatter,
F., Saxena, N., Lerman, K. & Galstyan, A. A Survey on Bias and
Fairness in Machine Learning. ACMComput. Surv. 54. issn:
0360-0300. https://doi.org/10.1145/3457607 (July 2021).
--
Alexandre Allauzen
✔️ @ApplyTime
ACM Computing Surveys
A Survey on Bias and Fairness in Machine Learning | ACM Computing Surveys
With the widespread use of artificial intelligence (AI) systems and applications in
our everyday lives, accounting for fairness has gained significant importance in designing
and engineering of such systems. AI systems can be used in many sensitive ...
our everyday lives, accounting for fairness has gained significant importance in designing
and engineering of such systems. AI systems can be used in many sensitive ...
PhD in International and Public Law, Ethics and Economics for Sustainable Development (LEES)
Università degli Studi di Milano
The PhD Programme in Law, Ethics & Economics for Sustainability (LEES) is an interdisciplinary Program of the University of Milan, characterised by a large network of international cooperation worldwide (see the list and the international scientific committee). The LEES aims at the creation of a global interdisciplinary research community that shares a commitment to the goals of sustainability.
Such a community will be devoted to promoting an interdisciplinary, integrated research approach to global concerns, able to foster a process of change in which the exploitation of resources, the direction of investments, the orientation of technological innovation, the model of economic development and organization, and the resulting institutional change, are all made consistent with the future, as well as the present needs of humankind, granting self-determination, equal treatment and social justice to each of its members, in harmony with the preservation of the ecosystem.
VACANCIES
3 Doctoral Research Positions in Law, Ethics and Economics for Sustainable Development (LEES)
The LEES program is seeking three outstanding and committed students to carry out a three-year multidisciplinary research project, based at more than one participating university (see the call for application and the course website).
We are launching LEES, a doctoral programme in International and Public Law, Ethics and Economics for Sustainable Development. With courses, seminars, and scientific research activities entirely in English, it addresses the complexities involved in sustainable development and uses an innovative multidisciplinary approach that combines the contributions of law, ethics, and economics.
--
Staff - Doctoral Programme
International and Public Law, Ethics and Economics for Sustainable Development - LEES
Website - lees@unimi.it
University of Milan
Via Festa del Perdono n° 7 - 20122 Milano, Italy
MailScanner Signature Unimi
La Statale per il futuro
Salute, transizione digitale, sostenibilità
Il tuo 5xmille ai nuovi progetti di ricerca dell’Università degli Studi di Milano
Codice fiscale: 80012650158
✔️ @ApplyTime
Università degli Studi di Milano
The PhD Programme in Law, Ethics & Economics for Sustainability (LEES) is an interdisciplinary Program of the University of Milan, characterised by a large network of international cooperation worldwide (see the list and the international scientific committee). The LEES aims at the creation of a global interdisciplinary research community that shares a commitment to the goals of sustainability.
Such a community will be devoted to promoting an interdisciplinary, integrated research approach to global concerns, able to foster a process of change in which the exploitation of resources, the direction of investments, the orientation of technological innovation, the model of economic development and organization, and the resulting institutional change, are all made consistent with the future, as well as the present needs of humankind, granting self-determination, equal treatment and social justice to each of its members, in harmony with the preservation of the ecosystem.
VACANCIES
3 Doctoral Research Positions in Law, Ethics and Economics for Sustainable Development (LEES)
The LEES program is seeking three outstanding and committed students to carry out a three-year multidisciplinary research project, based at more than one participating university (see the call for application and the course website).
We are launching LEES, a doctoral programme in International and Public Law, Ethics and Economics for Sustainable Development. With courses, seminars, and scientific research activities entirely in English, it addresses the complexities involved in sustainable development and uses an innovative multidisciplinary approach that combines the contributions of law, ethics, and economics.
--
Staff - Doctoral Programme
International and Public Law, Ethics and Economics for Sustainable Development - LEES
Website - lees@unimi.it
University of Milan
Via Festa del Perdono n° 7 - 20122 Milano, Italy
MailScanner Signature Unimi
La Statale per il futuro
Salute, transizione digitale, sostenibilità
Il tuo 5xmille ai nuovi progetti di ricerca dell’Università degli Studi di Milano
Codice fiscale: 80012650158
✔️ @ApplyTime
👍3
A Ph.D. student in bioengineering and robotics, University of Applied Sciences and Arts of Southern Switzerland - SUPSI, Switzerland
Research Assistant - Informatics (Prof. Haller), Free University of Bozen - Bolzano, Italy
PhD student: deep learning for cancer genomics, KU Leuven, Belgium
PhD Position in Political Economy, KU Leuven, Belgium
2 Postdoctoral Positions in (A) Digital Marketing and (B) Technology-based Services, IÉSEG School of Management, France
✅ If you are not interested in these positions, share them with your friends. You might change their life by simply sharing these!
✔️ @ApplyTime
🌐 https://applytime.ir
Research Assistant - Informatics (Prof. Haller), Free University of Bozen - Bolzano, Italy
PhD student: deep learning for cancer genomics, KU Leuven, Belgium
PhD Position in Political Economy, KU Leuven, Belgium
2 Postdoctoral Positions in (A) Digital Marketing and (B) Technology-based Services, IÉSEG School of Management, France
✅ If you are not interested in these positions, share them with your friends. You might change their life by simply sharing these!
✔️ @ApplyTime
🌐 https://applytime.ir
👍1