Research Associate on “Interpretable and Explainable Deep Learning for Natural Language Understanding and Commonsense Reasoning”
Applications for this vacancy closed on 4 January 2021 at 12:00PM
The Artificial Intelligence and Machine Learning group at the Department of
Computer Science has a vacancy for a Research Associate on “Interpretable and
Explainable Deep Learning for Natural Language Understanding and Commonsense
Reasoning”, funded by the Alan Turing Institute.
Reporting to Professor Thomas Lukasiewicz, you will be responsible for
carrying out research towards new approaches to interpretable and explainable
deep learning for natural language understanding and commonsense reasoning.
You will explore, generalise, and integrate deep learning approaches to
structured data extraction and to large-scale logic-based reasoning, towards
an interpretable and explainable deep-learning approach to human-like
understanding and commonsense reasoning in natural language processing, and to
investigate its applications in other disciplines, such as healthcare,
engineering, law, and finance. You will also collaborate with Professor
Lukasiewicz and members of his research group, providing guidance to junior
members of the research group, including PhD students, MSc students, and/or
project volunteers.
The primary selection criteria are a PhD degree in Computer Science,
Mathematics, Statistics, Engineering, Computational Linguistics, or related
discipline, together with relevant experience, in particular, possessing a
good (theoretical and programming) background in machine learning, and
knowledge representation and reasoning (desirably in deep learning and neural
networks, deep-learning-based representations, natural language processing,
and explainable and interpretable artificial intelligence), as well as good
software engineering skills (especially in system implementations and
experimental evaluations).
The closing date for applications is 12 noon on Monday 4th January 2021.
Our staff and students come from all over the world and we proudly promote a
friendly and inclusive culture. Diversity is positively encouraged, through
diversity groups and champions, for example
http://www.cs.ox.ac.uk/aboutus/women-cs-oxford/index.html, as well as a number
of family-friendly policies, such as the right to apply for flexible working
and support for staff returning from periods of extended absence, for example
maternity leave.
Computer Science has a vacancy for a Research Associate on “Interpretable and
Explainable Deep Learning for Natural Language Understanding and Commonsense
Reasoning”, funded by the Alan Turing Institute.
Reporting to Professor Thomas Lukasiewicz, you will be responsible for
carrying out research towards new approaches to interpretable and explainable
deep learning for natural language understanding and commonsense reasoning.
You will explore, generalise, and integrate deep learning approaches to
structured data extraction and to large-scale logic-based reasoning, towards
an interpretable and explainable deep-learning approach to human-like
understanding and commonsense reasoning in natural language processing, and to
investigate its applications in other disciplines, such as healthcare,
engineering, law, and finance. You will also collaborate with Professor
Lukasiewicz and members of his research group, providing guidance to junior
members of the research group, including PhD students, MSc students, and/or
project volunteers.
The primary selection criteria are a PhD degree in Computer Science,
Mathematics, Statistics, Engineering, Computational Linguistics, or related
discipline, together with relevant experience, in particular, possessing a
good (theoretical and programming) background in machine learning, and
knowledge representation and reasoning (desirably in deep learning and neural
networks, deep-learning-based representations, natural language processing,
and explainable and interpretable artificial intelligence), as well as good
software engineering skills (especially in system implementations and
experimental evaluations).
The closing date for applications is 12 noon on Monday 4th January 2021.
Our staff and students come from all over the world and we proudly promote a
friendly and inclusive culture. Diversity is positively encouraged, through
diversity groups and champions, for example
http://www.cs.ox.ac.uk/aboutus/women-cs-oxford/index.html, as well as a number
of family-friendly policies, such as the right to apply for flexible working
and support for staff returning from periods of extended absence, for example
maternity leave.
| dc:spatial |
Wolfson Building, Parks Road, Oxford.
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| oo:organizationPart | |
| vacancy:applicationClosingDate |
2021-01-04 12:00:00+00:00
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| vacancy:applicationOpeningDate |
2020-12-09 09:00:00+00:00
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| vacancy:furtherParticulars | |
| vacancy:internalApplicationsOnly |
False
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| vacancy:salary | |
| type | |
| comment |
The Artificial Intelligence and Machine Learning group at the Department of
Computer Science has a vacancy for a Research Associate on “Interpretable and Explainable Deep Learning for Natural Language Understanding and Commonsense Reasoning”, funded by the Alan Turing Institute. Reporting to Professor Thomas Lukasiewicz, you will be responsible for carrying out research towards new approaches to interpretable and explainable deep learning for natural language understanding and commonsense reasoning. You will explore, generalise, and integrate deep learning approaches to structured data extraction and to large-scale logic-based reasoning, towards an interpretable and explainable deep-learning approach to human-like understanding and commonsense reasoning in ... The Artificial Intelligence and Machine Learning group at the Department of Computer Science has a vacancy for a Research Associate on “Interpretable and Explainable Deep Learning for Natural Language Understanding and Commonsense Reasoning”, funded by the Alan Turing Institute. Reporting to Professor Thomas Lukasiewicz, you will be responsible for carrying out research towards new approaches to interpretable and explainable deep learning for natural language understanding and commonsense reasoning. You will explore, generalise, and integrate deep learning approaches to structured data extraction and to large-scale logic-based reasoning, towards an interpretable and explainable deep-learning approach to human-like understanding and commonsense reasoning in ... |
| label |
Research Associate on “Interpretable and Explainable Deep Learning for Natural Language Understanding and Commonsense Reasoning”
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| notation |
148608
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| based near | |
| page |