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

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7^th-8^th INTERNATIONAL CONFERENCE ON ALGORITHMS FOR COMPUTATIONAL BIOLOGY
 
AlCoB 2020 & 2021
 
Missoula, Montana, USA
 
June 7-11, 2021
 
Co-organized by:
 
Department of Computer Science
University of Montana
 
and
 
Institute for Research Development, Training and Advice – IRDTA
Brussels/London
 
https://irdta.eu/alcob2020-2021/
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AIMS:
 
AlCoB aims at promoting and displaying excellent research using string and graph algorithms and combinatorial optimization to deal with problems in biological sequence analysis, genome rearrangement, phylogeny reconstruction, and structure prediction.
 
AlCoB 2020 & 2021 will merge the scheduled program for AlCoB 2020, which could not take place because of the Covid-19 crisis, with a new series of papers submitted on this occasion.
 
Previous events were held in Tarragona, Mexico City, Trujillo (Spain), Aveiro, Hong Kong and Berkeley.
 
The conference will address several of the current challenges in computational biology, with topics including:
 
1) assembling sequence reads into a complete genome,
2) identifying gene structures in the genome,
3) recognizing regulatory motifs,
4) aligning nucleotides and comparing genomes,
5) reconstructing regulatory networks of genes, and
6) inferring the evolutionary phylogeny of species.
 
Special focus will be put on methodology and significant room will be reserved for scholars at the beginning of their career.
 
VENUE:
 
AlCoB 2020 & 2021 will take place in Missoula, Montana, a college town located in the heart of the Rocky Mountains, near Glacier National Park and Yellowstone National Park. The meeting will be hosted in the University Center, a few hundred feet from the base of Mount Sentinel.
 
SCOPE:
 
Topics of either theoretical or applied interest include, but are not limited to:
 
Sequence analysis
Sequence alignment
Sequence assembly
Genome rearrangement
Regulatory motif finding
Phylogeny reconstruction
Phylogeny comparison
Structure prediction
Compressive genomics
Proteomics: molecular pathways, interaction networks, mass spectrometry analysis
Transcriptomics: splicing variants, isoform inference and quantification, differential analysis
Next-generation sequencing: population genomics, metagenomics, metatranscriptomics, epigenomics
Genome CD architecture
Microbiome analysis
Cancer computational biology
Systems biology
 
STRUCTURE:
 
AlCoB 2020 & 2021 will consist of:
 
invited lectures
peer-reviewed contributions
posters
 
KEYNOTE SPEAKERS:
 
Terry Gaasterland (University of California, San Diego), Genetic Risk of Disease through Genome Variation and Regulation of Transcription
 
Christine Orengo (University College London), Algorithms for Mining Massive Metagenome Repositories to Detect Novel Enzymes
 
Tamar Schlick (New York University), Folding Genes at Nucleosome Resolution
 
PROGRAM COMMITTEE: (to be completed)
 
Ludmil Alexandrov (University of California, San Diego, US)
Can Alkan (Bilkent University, TR)
Mani Arumugam (University of Copenhagen, DK)
Bonnie Berger (Massachusetts Institute of Technology, US)
Chao Cheng (Baylor College of Medicine, US)
Colin Dewey (University of Wisconsin, Madison, US)
Ian Dunham (European Bioinformatics Institute, UK)
Joe Felsenstein (University of Washington, US)
Pedro G. Ferreira (University of Porto, PT)
Martin Frith (University of Tokyo, JP)
Debashis Ghosh (University of Colorado, US)
Michael Gribskov (Purdue University, US)
Michael Hawrylycz (Allen Institute for Brain Science, US)
Daniel Huson (University of Tübingen, DE)
Miriam Konkel (Clemson University, US)
Maria-Jesus Martin (European Bioinformatics Institute, UK)
Carlos Martín-Vide (Rovira i Virgili University, ES, chair)
David H. Mathews (University of Rochester, US)
Aaron McKenna (Dartmouth College, US)
Ryan E. Mills (University of Michigan, US)
Burkhard Morgenstern (University of Göttingen, DE)
Zemin Ning (Wellcome Sanger Institute, UK)
Joel S. Parker (University of North Carolina, Chapel Hill, US)
Kay Prüfer (Max Planck Institute for Evolutionary Anthropology, DE)
Knut Reinert (Free University of Berlin, DE)
Walter L. Ruzzo (University of Washington, US)
Russell Schwartz (Carnegie Mellon University, US)
Gordon Smyth (Walter and Eliza Hall Institute of Medical Research, AU)
Peter F. Stadler (Leipzig University, DE)
Alfonso Valencia (Barcelona Supercomputing Center, ES)
Fabio Vandin (University of Padua, IT)
Matthew T. Weirauch (Cincinnati Children's Hospital, US)
Travis Wheeler (University of Montana, US)
Zohar Yakhini (Interdisciplinary Center, Herzliya, IL)
Shibu Yooseph (University of Central Florida, US)
 
ORGANIZING COMMITTEE:
 
Sara Morales (Brussels)
Manuel Parra-Royón (Granada)
David Silva (London, co-chair)
Miguel A. Vega-Rodríguez (Cáceres)
Travis Wheeler (Missoula, co-chair)
 
SUBMISSIONS:
 
Authors are invited to submit non-anonymized papers in English presenting original and unpublished research. Papers should not exceed 12 single-spaced pages (all included) and should be prepared according to the standard format for Springer Verlag's LNCS series (see http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0).
 
Upload submissions to:
 
https://easychair.org/conferences/?conf=alcob20202021
 
PUBLICATIONS:
 
A volume of proceedings published by Springer in the LNCS/LNBI series will be available by the time of the conference.
 
A special issue of IEEE/ACM Transactions on Computational Biology and Bioinformatics (2019 JCR impact factor: 2.85) will be later published containing peer-reviewed substantially extended versions of some of the papers contributed to the conference. Submissions to it will be by invitation.
 
REGISTRATION:
 
The registration form can be found at:
 
https://irdta.eu/alcob2020-2021/registration/
 
DEADLINES (all at 23:59 CET):
 
Paper submission: January 18, 2021
Notification of paper acceptance or rejection: February 15, 2021
Final version of the paper for the LNCS/LNBI proceedings: March 1^st, 2021
Early registration: March 1^st, 2021
Late registration: May 24, 2021
Submission to the journal special issue: September 11, 2021
 
QUESTIONS AND FURTHER INFORMATION:
 
david (at) irdta.eu
 
ACKNOWLEDGEMENTS:
 
University of Montana
 
IRDTA – Institute for Research Development, Training and Advice, Brussels/London
  

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