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 –  https://www.jobbnorge.no/en/available-jobs/job/192788/1-2-phd-fellows-in-computer-science-artificial-intelligence-for-virtual-staining-of-label-free-cell-and-tissue-images    

Deadline – 18th October 2020
Location– Tromsø, Norway

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

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

Requirement:
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 available.

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