Connectionists: [Job] Postdoc in deep learning for medical image analysis, KTH Royal Institute of Technology, Stockholm

[Kevin Smith]

Job description

This position is part of a collaboration with physicians from the
Karolinska University Hospital. The main task will be to develop deep
learning methods to analyse medical images, focusing on breast cancer. The
successful applicant will apply his/her knowledge in deep learning to
several types of medical images, including histological sections,
mammograms, and possibly others. Generally, the goal will be towards
predicting patient outcome, but we aim to develop models for specific
predictors of patient outcome, such as tumour heterogeneity biomarkers and
risk models. In additional to these medical applications, the successful
candidate will also participate in theoretical research in deep learning
and computer vision. Other duties include helping to mentor MSc and PhD
students, and potential teaching duties.

The position is initially funded for one year, with a possibility for
extension contingent upon funding and eligibility.

Qualifications

Candidates must have a PhD in computer science, computational science, or a
related field received within the last three years. Proven knowledge and
ability in one or more deep learning frameworks (Tensorflow, Keras, Torch,
Caffe, etc) is absolutely required. Also required is knowledge of standard
computer vision techniques and experience in implementing, analysing, and
optimizing scientific applications for image analysis. Proficiency in one
or two scientific computing languages (Python, Matlab, R) is required.
Experience with parallel programming environments and cloud computing is a
plus. Previous experience working with medical or biological images is also
desirable.


*KTH Royal Institute of Technology*

KTH Royal Institute of Technology in Stockholm has grown to become one of
Europe’s leading technical and engineering universities, as well as a key
centre of intellectual talent and innovation. We are Sweden’s largest
technical research and learning institution and home to students,
researchers and faculty from around the world. Our research and education
covers a wide area including natural sciences and all branches of
engineering, as well as in architecture, industrial management, urban
planning, history and philosophy.



For information about the School of Computer Science and Communication,
please visit https://www.kth.se/en/csc.

Department information

The position will be formally placed with the department for Computational
Science and Technology (CST) at KTH, but work will be carried out at the
Science for Life Laboratory. The CST department conducts research to
understand and model physical and biological systems using computational
techniques, which require efficient, high performance algorithms and
implementations together with advanced visual analysis capabilities. For
more information go to https://www.kth.se/en/csc/forskning/cst.


The Science for Life Laboratory (SciLifeLab) is a collaboration between
four universities in Stockholm and Uppsala: Karolinska Institutet, KTH,
Stockholm University and Uppsala University. It combines advanced
technology with broad knowledge in translational medicine and molecular
life sciences. Since 2013, SciLifeLab has a mission from the Swedish
government to run infrastructure to support researchers nationally and to
be an internationally leading center for large-scale analyses in molecular
life sciences targeting research in health and environment. For more
information, visit https://www.scilifelab.se/.

Trade union representatives

You will find contact information to trade union representatives at KTH:s
webbpage
<http://intra.kth.se/en/administration/rekrytering/annonsering/fackrepresentanter-1.500898>
.

Application

Log into KTH's recruitment system in order to apply to this position. You
are the main responsible to ensure that your application is complete
according to the ad.

Your complete application must be received at KTH no later than the last
day of application, midnight CET/CEST (Central European Time/Central
European Summer Time).

Applications shall include the following documents:

   1.

   Statement of interest including a brief description of experience in
   deep learning
   2.

   Curriculum vitae
   3.

   Transcripts from university
   4.

   Reference contact information
   5.

   Representative publications (or other example of scientific writing)

Please observe that all material needs to be in English.

Others

We firmly decline all contact with staffing and recruitment agencies and
job ad salespersons.

Disclaimer: In case of discrepancy between the Swedish original and the
English translation of the job announcement, the Swedish version takes
precedence.

Type of employment

Temporary position longer than 6 months

Contract type

Full time

First day of employment

According to the agreement

Salary

Monthly salary

Number of positions

1

Working hours

100%

City

Solna

County

Stockholms län

Country

Sweden

Reference number

D-2017-0814


Contact

   -

   Kevin Smith / Bitr universitetslektor, ksmith at kth.se, +46 8 790 64 37
   -

   Maria Engman / HR-administratör, maengm at kth.se

Published

14.Nov.2017

Last application date

06.Jan.2018 11:59 PM CET
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