POSITION DETAILS:
Research Fellow/Senior Research Fellow in Visualisation
Job reference: 001367
Employment type: Full part time, 36 month fixed term contract
Classification: Research level BRF/CSRF
Salary range: $85,602 - $120,916 per annum
Your total remuneration will include the above salary plus employer superannuation contributions of up to 17% of salary, and annual leave loading. See more benefits of working for UniSA
http://www.unisa.edu.au/About-UniSA/Working-at-UniSA/Vacancies/
School of Information Technology & Mathematical Sciences, Division of
Information Technology, Engineering and the Environment, University of South Australia
LOCATION:
Mawson Lakes Campus
Please note: appointment is to the University. The appointee may be required to undertake duties at other locations.
FURTHER INFORMATION:
Professor Bruce Thomas
Telephone: +61 8 8302 3464
Email: bruce.thomas@unisa.edu.au
CLOSING DATE:
9.00am Tuesday 9 September 2014
LODGEMENT DETAILS:
Applications must be lodged online through Working at UniSA at
Research Fellow/Senior Research Fellow in Visualisation (level BRF/CSRF)Job Ref - 001367
http://www.unisa.edu.au/About-UniSA/Working-at-UniSA/Vacancies/
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For further support contact the Recruitment Hub on (08) 8302 1700 or email recruitment@unisa.edu.au and you will receive a response within one working day.
POSITION DESCRIPTION
Research Fellow / Senior Research Fellow in Visualisation
Advanced Computing Research Centre
School of Information Technology & Mathematical Sciences
Division of Information Technology, Engineering and the Environment
Mawson Lakes Campus
Level BRF/CSRF
3 year fixed term contract
PURPOSE OF POSITION
The Research Fellow / Senior Research Fellow in Visualisation will contribute to the research efforts of the Advanced Computing Research Centre and the School of ITMS, and will develop their expertise through defined research projects linked to the Data to Decisions Cooperative Research Centre (D2D CRC).
The objective is the investigation into visualisation of “Big data” sets. Big data is a collection of data and information sets so large they are difficult to store, search and analyse using traditional processing applications. This project will investigate novel man-machine visualisation tools for extremely large data sets that also cater for a wide variety of information forms.
The first innovation is to support a user’s critical ability to maintain a clear working memory with a manageable cognitive load whilst exploring large data sets. Recalling information for reasoning and comprehension is crucial to successfully exposing hidden information. However, current approaches require users to recognise and memorise hundreds of graph nodes; this is well beyond a reasonable cognitive load. This problem has only become evident, as the size of data sets has rapidly changed from hundreds to millions of nodes. This investigation explores how principles from cognitive psychology can be used in graph visualization to reduce this load by employing physical memory aids, lists and abstract model presentation approaches, with graph sizes of 10,000’s to 100,000’s nodes.
The second innovation is to describe complex and varying data sources in an understandable and productive manner. Data is collected from sources including unstructured data such as: video surveillance, passport photographs, weather reports, news services, and textual messages, but equally there are structured sources such as the following: social networks, telephone records, passport control, and flight manifests. This information and data requires a meta-level of structure for the user. This is useful where the user is required to provide support for the organisation to present wide and varied forms of information.
martes, 26 de agosto de 2014
PhD position in visualization at Inria Saclay, France (20km from Paris): Visualization of structural and functional connectivity in the brain
PDF version:
http://www.aviz.fr/wiki/uploads/Research/2014_AVIZ_PhD_Project_-_BrainVis.pdf
application deadline: September 15, 2014
starting date: end of 2014 at the latest
Description:
The study of brain connectivity is one of the fundamental ways to
investigate the complex functions of the (human) brain. For this purpose,
neuroanatomists capture and investigate two different types of
connectivity: anatomical connectivity arising from diffusion-weighted MRI
measurements and functional connectivity based on fMRI scans. Both types of
data have advantages and disadvantages, but ultimately it is essential to
study them in concert.
The research project:
The research in this PhD project will employ and combine approaches from two
sub-fields of visualization: the visualization of spatial relationships
(SciVis, for anatomical connectivity) and the visualization of abstract data
(InfoVis, for functional connectivity data). The goal is to be able to start
the interactive investigation with either type of data, being able to
interactively and freely switch between the different representations as it
is needed for the data exploration. The ultimate vision is two-fold: The
first and foremost aspect is to get to a more in-depth understanding on how
to support interactive data exploration using various new and
state-of-the-art visualization techniques in the neurosciences. The second
aspect is that to more generally push the boundaries of multimodal
visualization to be able to generalize the findings of this research to
other fields that work on a daily basis with data that has both spatial and
abstract characteristics.
For this purpose the project extends past results in the visualization of
dense line data as well as the visualization of weighted graphs. For the
first aspect of anatomical connectivity, the project will use methods from
illustrative visualization to deal with the dense fibertract datasets that
are generated from diffusion-weighted MRI. This aspect of the visualization
will provide an important visual reference and landmark for the exploration
of functional connectivity, for which the project will rely on the
visualization of weighted graphs. A general challenge in this context is the
question on how to create a visualization that combines both data types,
either in separate views or in a combined view. Separate linked views are
common in abstract data visualization and we will thus explore their
application for our application. A view that integrates both could combine
fibertracts inside the brain for anatomical connectivity with a bundled view
of functional links on its outside. This approach has the potential benefit
of not requiring a mental integration of separate points of reference.
On the other hand, this approach may lead to a cluttered and overloaded
depiction. The project will therefore explore new ways of controlling the
abstraction in the data depiction to deal with this issue to be able to show
the realistic large and complex datasets. This work will thus also require
research to understand how to apply illustrative visualization to abstract
data.
Such visualizations of the fibertracts in a more or less realistic way is
convenient for the neuroscientist, but we have to consider other
complementary linked views. These views often do not match the realistic
physical appearance of fibertracts but instead focus on the task at hand the
neuroscientist wants to perform with the data. So other representations than
graphs will be explored as part of this project such as scatter plots or
space-filling or pixel-based designs enabling to provide a mapping of the
information space more efficient to solve a specific visual analytic task.
Machine learrning techniques such as generative graphs will be used to
automatically extract summaries of the anatomical and functional
connectivity data. These geometrical and topological summaries will be used
as a backbone structure for the visualization of the information space to be
used for visual analysis tasks.
Moreover, an integral aspect of our approach is to combine the visualization
techniques in an interactive exploration tool that supports analists in
adjusting their exploration strategy as needed. An integral part of the
neuroanatomists' data exploration is the comparison of different datasets,
either derived from different people or captured at different points in
time. Therefore, the comparison of different datasets and the temporal
exploration will be an essential aspect of the project. To be successful in
this project, the PhD student will work closely with domain experts in the
neurosciences from the Université Pierre et Marie Curie, both to develop the
integrated interactive visualization techniques using a participatory design
approach as well as to evaluate the new techniques in controlled
experiements.
By closely working with the domain experts, the PhD student will work toward
an interactive tool for neuroanatomical data exploration that integrates the
new visualization techniques. The goal for this tool is that it can be used
in a realistic context for the everyday analysis tasks of the
neuroanatomists and that it will be provided to the public as open-source
software. Beyond this implementation, the project will result in a deeper
understanding of how to combine spatially explicit data with connected
abstract data aspects to benefit visualization in the sciences in general.
The PhD research will be conducted under the supervision of Tobias Isenberg
and within the AVIZ research team at INRIA Saclay—Île-de-France which
concentrates on the visualization of complex data. AVIZ is one of the most
respected research labs in information visualization and visual analytics
worldwide. The PhD student will closely collaborate, in particular, with
Cédric Gouy-Pailler from the Laboratoire Analyse de Données et Intelligence
des Systèmes at CEA whose expertise in machine learning will be essential
for the work. In addition, we will work with domain experts in the
neurosciences from the Université Pierre et Marie Curie.
Required applicants skills:
* highly motivated student
* degree (M.Sc., M. Eng, or equivalent) in computer science or closely
related fields
* education background in one or more of the following fields:
visualization, human-computer interaction, computer graphics, and machine
learning
* interest in applications in neuroimaging or in knowledge discovery
* previous experience in these fields (in particular, neuroimaging) would be
highly beneficial
* experience in modern computer graphics (GPU) programming
* fluent in written and spoken English (French language skills are not
required but would be beneficial for living in France and interacting with
people outside of the lab)
* previous experience in research and publication of research results
beneficial
Application package:
* detailed CV
* motivation letter
* summary of the master thesis
* transcript of the grades
* contact details for two academic references
* prepare all application documents electronically and in English
* application deadline: applications are reviewed as they are received;
however, for full consideration please submit your application by September
15
Contact:
Dr. Tobias Isenberg
(http://tobias.isenberg.cc/)
Group:
AVIZ team, INRIA Saclay (20km from Paris)
(http://www.aviz.fr/)
http://www.aviz.fr/wiki/uploads/Research/2014_AVIZ_PhD_Project_-_BrainVis.pdf
application deadline: September 15, 2014
starting date: end of 2014 at the latest
Description:
The study of brain connectivity is one of the fundamental ways to
investigate the complex functions of the (human) brain. For this purpose,
neuroanatomists capture and investigate two different types of
connectivity: anatomical connectivity arising from diffusion-weighted MRI
measurements and functional connectivity based on fMRI scans. Both types of
data have advantages and disadvantages, but ultimately it is essential to
study them in concert.
The research project:
The research in this PhD project will employ and combine approaches from two
sub-fields of visualization: the visualization of spatial relationships
(SciVis, for anatomical connectivity) and the visualization of abstract data
(InfoVis, for functional connectivity data). The goal is to be able to start
the interactive investigation with either type of data, being able to
interactively and freely switch between the different representations as it
is needed for the data exploration. The ultimate vision is two-fold: The
first and foremost aspect is to get to a more in-depth understanding on how
to support interactive data exploration using various new and
state-of-the-art visualization techniques in the neurosciences. The second
aspect is that to more generally push the boundaries of multimodal
visualization to be able to generalize the findings of this research to
other fields that work on a daily basis with data that has both spatial and
abstract characteristics.
For this purpose the project extends past results in the visualization of
dense line data as well as the visualization of weighted graphs. For the
first aspect of anatomical connectivity, the project will use methods from
illustrative visualization to deal with the dense fibertract datasets that
are generated from diffusion-weighted MRI. This aspect of the visualization
will provide an important visual reference and landmark for the exploration
of functional connectivity, for which the project will rely on the
visualization of weighted graphs. A general challenge in this context is the
question on how to create a visualization that combines both data types,
either in separate views or in a combined view. Separate linked views are
common in abstract data visualization and we will thus explore their
application for our application. A view that integrates both could combine
fibertracts inside the brain for anatomical connectivity with a bundled view
of functional links on its outside. This approach has the potential benefit
of not requiring a mental integration of separate points of reference.
On the other hand, this approach may lead to a cluttered and overloaded
depiction. The project will therefore explore new ways of controlling the
abstraction in the data depiction to deal with this issue to be able to show
the realistic large and complex datasets. This work will thus also require
research to understand how to apply illustrative visualization to abstract
data.
Such visualizations of the fibertracts in a more or less realistic way is
convenient for the neuroscientist, but we have to consider other
complementary linked views. These views often do not match the realistic
physical appearance of fibertracts but instead focus on the task at hand the
neuroscientist wants to perform with the data. So other representations than
graphs will be explored as part of this project such as scatter plots or
space-filling or pixel-based designs enabling to provide a mapping of the
information space more efficient to solve a specific visual analytic task.
Machine learrning techniques such as generative graphs will be used to
automatically extract summaries of the anatomical and functional
connectivity data. These geometrical and topological summaries will be used
as a backbone structure for the visualization of the information space to be
used for visual analysis tasks.
Moreover, an integral aspect of our approach is to combine the visualization
techniques in an interactive exploration tool that supports analists in
adjusting their exploration strategy as needed. An integral part of the
neuroanatomists' data exploration is the comparison of different datasets,
either derived from different people or captured at different points in
time. Therefore, the comparison of different datasets and the temporal
exploration will be an essential aspect of the project. To be successful in
this project, the PhD student will work closely with domain experts in the
neurosciences from the Université Pierre et Marie Curie, both to develop the
integrated interactive visualization techniques using a participatory design
approach as well as to evaluate the new techniques in controlled
experiements.
By closely working with the domain experts, the PhD student will work toward
an interactive tool for neuroanatomical data exploration that integrates the
new visualization techniques. The goal for this tool is that it can be used
in a realistic context for the everyday analysis tasks of the
neuroanatomists and that it will be provided to the public as open-source
software. Beyond this implementation, the project will result in a deeper
understanding of how to combine spatially explicit data with connected
abstract data aspects to benefit visualization in the sciences in general.
The PhD research will be conducted under the supervision of Tobias Isenberg
and within the AVIZ research team at INRIA Saclay—Île-de-France which
concentrates on the visualization of complex data. AVIZ is one of the most
respected research labs in information visualization and visual analytics
worldwide. The PhD student will closely collaborate, in particular, with
Cédric Gouy-Pailler from the Laboratoire Analyse de Données et Intelligence
des Systèmes at CEA whose expertise in machine learning will be essential
for the work. In addition, we will work with domain experts in the
neurosciences from the Université Pierre et Marie Curie.
Required applicants skills:
* highly motivated student
* degree (M.Sc., M. Eng, or equivalent) in computer science or closely
related fields
* education background in one or more of the following fields:
visualization, human-computer interaction, computer graphics, and machine
learning
* interest in applications in neuroimaging or in knowledge discovery
* previous experience in these fields (in particular, neuroimaging) would be
highly beneficial
* experience in modern computer graphics (GPU) programming
* fluent in written and spoken English (French language skills are not
required but would be beneficial for living in France and interacting with
people outside of the lab)
* previous experience in research and publication of research results
beneficial
Application package:
* detailed CV
* motivation letter
* summary of the master thesis
* transcript of the grades
* contact details for two academic references
* prepare all application documents electronically and in English
* application deadline: applications are reviewed as they are received;
however, for full consideration please submit your application by September
15
Contact:
Dr. Tobias Isenberg
(http://tobias.isenberg.cc/)
Group:
AVIZ team, INRIA Saclay (20km from Paris)
(http://www.aviz.fr/)
4yr PhD studentship in 3D Mass Digitization/Metadata for Cutural Heritage (UK/Ger)
PhD studentship opportunity: Mass digitization and metadata enrichment of 3D cultural heritage artefacts by automatic and user-based metadata acquisition
Applications are invited for a four year fully-funded PhD studentship within EPSRC Centre for Doctoral Training in Science and Engineering in Arts, Heritage and Archaeology (SEAHA – www.seaha-cdt.ac.uk) . The studentship comprises a one-year MRes based at UCL, London, followed by three years PhD study at the University of Brighton, in collaboration with the Fraunhofer Institute for Computer Graphics Research (Darmstadt, Germany) and the Brighton Royal Pavilion and Museums. The project will look at the state-of-the-art ‘conveyor belt’ approach to high fidelity 3D digitization of complex cultural artefacts. Effective management and exploration of collections depends on the acquisition not just of the artefacts themselves, but also of semantic metadata, providing annotation of, and linkage between, acquired assets in the collection. This PhD project aims to explore the potential for the application of mass digitization technology in cultural heritage organisations, and to develop tools and techniques for the enrichment of collections with metadata by automatic and user-based acquisition.
Application deadline: open until filled, for Sep 22 start on MRes at UCL
Detailed information:
As a SEAHA student, you will have unparalleled access to research infrastructure and expertise across three universities and almost 50 heritage, research and industrial partners. In addition to the university doctoral training requirements, SEAHA students take part in an exciting range of cohort activities, ranging from residential events and group projects, to conferences and careers events.
Please visit the SEAHA website (www.seaha-cdt.ac.uk) for details.
This exceptionally interdisciplinary project will enable you to seek employment in any number of multidisciplinary environments: from academia to creative industries. You will have an outstanding record in aspects of computer science related to the project (consistent with a first or upper-second in Computing Science) and will be able to demonstrate knowledge and commitment within a cultural context. Excellent proficiency in the English language is mandatory and knowledge of the German language is encouraged. Professional experience in industry would be an advantage. For further details contact Dr. Roger Evans, R.P.Evans@brighton.ac.uk.
The SEAHA Studentship will cover home fees and a stipend of up to a maximum of £16,726 per year (current rate) for eligible applicants (http://www.seaha-cdt.ac.uk/opportunities/eligibility-criteria/), and a substantial budget for research, travel, and cohort activities.
The application should include:
- A covering letter clearly stating your motivation
- The UCL graduate application form which can be downloaded via UCL's web site: http://www.ucl.ac.uk/prospective-students/graduate/apply/apply-now/ucl-graduateapplication-form.pdf
- Two academic references
- A copy of your degree certificate(s) and transcript(s) of degree(s),
- Proof of meeting the UCL English language proficiency requirements where necessary. For SEAHA candidates, an advanced level certificate is normally required (details of English language proficiency requirements can be found at http://www.ucl.ac.uk/prospectivestudents/ graduate/apply/english-language/index)
- A short research proposal (max. 2000 words) written by taking into consideration the above research questions.
The applications should not be submitted by UCL online admissions system. Instead, they should be sent directly to:
SEAHA Manager
manager@seaha-cdt.ac.uk
UCL Centre for Sustainable Heritage
Faculty of the Built Environment UCL
14 Upper Woburn Place
LondonWC1E 0NN
UCL Taking Action For Equality.
Application deadline: 1200 (noon) 13 August 2014; thereafter the position will remain open for applications until filled. Interviews are expected to take place in the first week of September.
Applications are invited for a four year fully-funded PhD studentship within EPSRC Centre for Doctoral Training in Science and Engineering in Arts, Heritage and Archaeology (SEAHA – www.seaha-cdt.ac.uk) . The studentship comprises a one-year MRes based at UCL, London, followed by three years PhD study at the University of Brighton, in collaboration with the Fraunhofer Institute for Computer Graphics Research (Darmstadt, Germany) and the Brighton Royal Pavilion and Museums. The project will look at the state-of-the-art ‘conveyor belt’ approach to high fidelity 3D digitization of complex cultural artefacts. Effective management and exploration of collections depends on the acquisition not just of the artefacts themselves, but also of semantic metadata, providing annotation of, and linkage between, acquired assets in the collection. This PhD project aims to explore the potential for the application of mass digitization technology in cultural heritage organisations, and to develop tools and techniques for the enrichment of collections with metadata by automatic and user-based acquisition.
Application deadline: open until filled, for Sep 22 start on MRes at UCL
Detailed information:
As a SEAHA student, you will have unparalleled access to research infrastructure and expertise across three universities and almost 50 heritage, research and industrial partners. In addition to the university doctoral training requirements, SEAHA students take part in an exciting range of cohort activities, ranging from residential events and group projects, to conferences and careers events.
Please visit the SEAHA website (www.seaha-cdt.ac.uk) for details.
This exceptionally interdisciplinary project will enable you to seek employment in any number of multidisciplinary environments: from academia to creative industries. You will have an outstanding record in aspects of computer science related to the project (consistent with a first or upper-second in Computing Science) and will be able to demonstrate knowledge and commitment within a cultural context. Excellent proficiency in the English language is mandatory and knowledge of the German language is encouraged. Professional experience in industry would be an advantage. For further details contact Dr. Roger Evans, R.P.Evans@brighton.ac.uk.
The SEAHA Studentship will cover home fees and a stipend of up to a maximum of £16,726 per year (current rate) for eligible applicants (http://www.seaha-cdt.ac.uk/opportunities/eligibility-criteria/), and a substantial budget for research, travel, and cohort activities.
The application should include:
- A covering letter clearly stating your motivation
- The UCL graduate application form which can be downloaded via UCL's web site: http://www.ucl.ac.uk/prospective-students/graduate/apply/apply-now/ucl-graduateapplication-form.pdf
- Two academic references
- A copy of your degree certificate(s) and transcript(s) of degree(s),
- Proof of meeting the UCL English language proficiency requirements where necessary. For SEAHA candidates, an advanced level certificate is normally required (details of English language proficiency requirements can be found at http://www.ucl.ac.uk/prospectivestudents/ graduate/apply/english-language/index)
- A short research proposal (max. 2000 words) written by taking into consideration the above research questions.
The applications should not be submitted by UCL online admissions system. Instead, they should be sent directly to:
SEAHA Manager
manager@seaha-cdt.ac.uk
UCL Centre for Sustainable Heritage
Faculty of the Built Environment UCL
14 Upper Woburn Place
LondonWC1E 0NN
UCL Taking Action For Equality.
Application deadline: 1200 (noon) 13 August 2014; thereafter the position will remain open for applications until filled. Interviews are expected to take place in the first week of September.
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