[visionlist] 1-2 Fully funded (4yrs) PhD position on AI/machine learning @ UiT The Arctic University of Norway

Dilip K. Prasad dilipprasad at gmail.com
Thu Oct 1 05:40:50 -04 2020

1-2 Fully funded (4yrs) PhD position on AI/machine learning with the
Department of Computer Science, UiT The Arctic University of Norway.

*Application Link* -

*Deadline* - 18th October 2020
*Location*- Tromsø, Norway

These positions require a Master’s degree or equivalent in Computer
Science, or Mathematics and Computing. In addition, the candidates must

Experience of working with computer vision and deep learning toolkits on at
least one of the following platforms – Python, C/C++, MATLAB, Keras,
PyTorch, Tensor Flow

Demonstration of programming proficiency in at least two of the following
platforms: Python, C/C++, MATLAB, OpenCV, etc.

Postgraduate coursework or master thesis strongly related to at least four
of the following topics:

- Machine learning/deep learning
- Computer vision
- Optimization theory/ convex optimization/computational optimization
- Linear algebra
- Statistics/statistical machine learning
- Computational modelling of differential and integral equations
- Data science
- GPU programming
- Neural networks
- Distributed learning/extreme learning

Your application must include:
Cover letter explaining your motivation and research interests
CV - summarizing education, positions and academic work
Diplomas and transcripts from completed Bachelor’s and Master’s degrees
Documentation of English proficiency
1-3 references with contact details
Master thesis, and any other academic works
Documentation has to be in English or a Scandinavian language. We only
accept applications through Jobbnorge.

*Remuneration* - approx. 48,000 Euro per annum (Remuneration of the PhD
position is in State salary scale code 1017. A compulsory contribution of
2% to the Norwegian Public Service Pension Fund will be deducted.)

*Description *- VirtualStain is a project funded under thematic call for
strategic funding by UiT The Arctic University of Norway. It involves
developing AI solutions for segmenting, identity allocation, and modeling
of the processes of sub-cellular structures such as mitochondria in cells
and cellular structures in tissues using label-free images and videos of
cells and tissues. Interpreting life processes and label-free images of
cells and tissues is a daunting task. The PhD students will work on the
following problem:

Images of unlabeled samples appear as gray scale images devoid of color,
texture, and edges. Therefore, they lack features conventionally used in
deep models for identification of individual structures. New suitably
designed and trained intelligence models have to be developed specific to
the chosen label-free imaging technology. If conventional AI approaches
such as deep learning and generative networks are used, large training
dataset with correlated image sets of labeled and label-free images are
needed, which is a significant challenge. There is a need of new out-of-box
AI solutions that derive and improve intelligence, as new data becomes

*Project page* - https://en.uit.no/project/virtualstain

best regards
Dilip K. Prasad
Associate Professor,
Department of Computer Science
UiT The Arctic University of Norway
Tromsø, Norway
Scholar - https://scholar.google.com.sg/citations?user=a6ZNU7EAAAAJ&hl=en
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