Post doctor (2 years) within graph-based machine learning - Befattningen är under tillsättning eller redan tillsatt, och det är inte längre möjligt att lämna in en ansökan

The Department of Computing science seeks a postdoctor to join the project Semantic Parsing of Multimodal Data. The employment is full-time for two years with access March 1, 2023, or by agreement.

Department of Computing science 
The Department of Computing Science is characterized by world-leading research in a multitude of scientific fields, and is ranked highly in international comparison. The department has been growing rapidly in recent years, with a focus on creating an inclusive and bottom-up driven research environment. To further strengthen our numbers, we are now looking for a postdoctor in graph-based machine learning for multimodal parsing. Our workplace consists of a diverse set of people from different nationalities, background and fields. If you work as a postdoctor with us, you receive the benefits of support in career development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available at:

https://www.umu.se/en/department-of-computing-science/

Is this interesting for you? Welcome with your application before 2022-12-31.

Project description and working tasks 
The research project is funded by the Swedish Research Council (VR) and serves to develop novel graph-based methods for semantic parsing of multimodal data. In other words, the translation of composite media items such as a video with audio tracks and subtitles, or a digital news article with text and images, into structured representations that capture central aspects of the combined media. The problem appears in many technological areas. In robotics, it takes the form of language grounding, where the linguistic constituents of a natural language command are linked to real-world objects, attributes, and relations. In media asset management, it appears as automatic captioning of images. It is also of inherent value in machine learning, because it allows us to transfer knowledge between different modalities. Knowledge that we have learnt from text can, e.g., be used to understand images.

The outcome of the project is a theory of graph-based computation tailored for multimodal parsing.  This consists of formal graph languages to represent the data, together with transition-based computation models that operate on such representations.  In their classical form, these models have finite sets of discrete states, but some of the best performing existing semantic parsers combine transition-based models with recursive neural networks.  In these modern hybrid models, the state space is the Cartesian product of a discrete state space and the continuous, potentially unbounded, state space of a neural network.

Possible research directions for the postdoctor are:

·         Attention-based models for translation from e.g., text and audio, into semantic graphs

·         Discrete and continuous methods for fusing and restructuring graph representations

The project is conducted within the research group for the Foundations of Language Processing at Umeå University, and is led by Associate Professor Johanna Björklund. The group studies theoretical and practical aspects of representing language on computers, and its interconnection with other sources of information. The work of the group spans from formal language theory to applied natural language processing. The group consists of 5 senior researchers and 8 PhD students. More information is available at:

https://www.umu.se/en/research/groups/foundations-of-language-processing/

The work will be carried out in collaboration with the recently initiated WASP NEST project STING - Synthesis and analysis with Transducers and Invertible Neural Generators, with PIs at Umeå University, Linköping University, and KTH. Read more about the NEST project at: 

https://wasp-sweden.org/sting-synthesis-and-analysis-with-transducers-and-invertible-neural-generators/

Qualifications 

This section states the formal requirements UmU has on a post doctor in accordance with the UmU Appointment Procedure for Teachers (FS 1.1-129-22), as well as the specific requirements that connected to the project.

To be appointed under the postdoctoral agreement, the postdoctoral fellow is required to have completed a doctoral degree or a foreign degree deemed equivalent to a doctoral degree. This qualification requirements must be fulfilled no later than at the time of the appointment decision.

To be appointed under the postdoctoral agreement, priority should be given to candidates who completed their doctoral degree, according to what is stipulated in the paragraph above, no later than three years prior. If there are special reasons, candidates who completed their doctoral degree prior to that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organizations, military service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant to the subject area. Postdoctoral fellows who are to teach or supervise must have taken relevant courses in teaching and learning in higher education

The postdoctor must have experience of 

·         Formal language theory 

·         Machine learning

Other desirable qualifications include experience of

·         Natural language processing

·         Formal graph languages

·         Graph representation learning

·         Empirical methods, i.e., formal hypothesis testing

Application 
 

A full application should include:

-          Cover letter in which you explain why you are interested in the research project and how you think you could contribute,

-          Curriculum vitae (CV) with publication list,

-          Verified copy of doctoral degree certificate or documentation that clarifies when the degree of doctor is expected to be obtained,

-          Copy of doctoral thesis and, optionally, up to 3 relevant articles,

-          Other documents that the applicant wishes to claim, 

-          Contact information to two persons willing to act as references.

The application must be written in English or Swedish. The application is made through our electronic recruitment system. Documents sent electronically must be in Word or PDF format. Log in to the system and apply via the button at the end of this page. The closing date is 2022-12-31.

Further details are provided by Johanna Björklund, johanna@cs.umu.se, +4670 603 94 59.