PhD student in deep learning

KTY Royal Institute of Technology
Location: 
Stockholm, Sweden
Job Type: 
Full Time
Closing Date: 
Tuesday, August 15, 2017

Job description:

Deep learning, as a field of machine learning, has dramatically pushed the performance of many intelligent systems, but many important questions remain open for research. How should one interpret its decision making process? Can one successfully learn deep learning models without large-scale annotated data? What are the limits of its application to other fields?

The role of the doctoral student will be to focus on developing theoretical advances regarding these research questions and/or applying them to general computer vision and, to a lesser extent, natural language processing. A secondary aspect involves applications with medical data. Medical data analysis is attracting attention from top players in various fields as more data and resources become available (such as Medical Imagenet by Stanford University). We will look for ways to apply the methods we develop in many exciting medical applications such as automatic diagnosis, personalized drug discovery, genetic analysis, and so forth.

The specific research topics may include but are not limited to using adversarial training for unsupervised and semi-supervised learning as well as domain adaptation, uncertainty estimation of a deep network’s output, understanding deep networks and its inner workings, and applying state-of-the-art models to highly impactful medical applications such as cancer prediction in medical data. Should the student be willing and experienced enough in deep learning, she/he will have some freedom to steer the direction of research.

This is a four (4) year time-limited position with full funding and support for travel to conferences, etc. It can be extended up to five (5) years with the inclusion of a maximum of 20% departmental duties, typically teaching.

In order to be employed, you must apply and be accepted as a doctoral student at KTH. The starting date is open for discussion, though we would like the successful candidate to start as soon as possible.
Qualifications:

A Bachelor of Science degree in Computer Science or a closely related field is required. Preference will be given to applicants with a Master's degree or current Master students who are about to complete their degree.

Applicants should have a good knowledge of English and ability to express themselves clearly both in speech and writing. The successful candidate must be strongly motivated for doctoral studies, must have demonstrated the ability to work independently and to perform critical analysis. They must also possess excellent cooperative and communication skills.

Of highest importance is prior experience/education in both theory and practice of machine learning, specially deep learning. We prefer experienced users of deep learning frameworks such as TensorFlow, Torch, Keras, Theono, Caffe, CNTK, MXNet. Proficiency in one or two scientific computing language(s) (R, Matlab, Python) is required.

Also desirable is prior experience with parallel programming environments, familiarity with Linux administration, experience with image analysis (especially medical or microscopy), experience with C++ programming, and working with remote HPC and cloud services.

Application:

Log into KTH's recruitment system in order to apply to this position (https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:156210/w...). You are responsible to ensure that your application is complete according to the ad.

Applications shall include the following documents:

1. Statement of interest and brief description of experience in machine learning, and/or deep learning, computer vision, and natural language processing.
2. Curriculum vitae
3. Transcripts from university/university college
4. Letter of recommendation and contact information from two references
5. An example of the applicant’s original technical writing, e.g., thesis, technical report, or scientific paper

Please observe that all material needs to be in English.

Your complete application must be received at KTH no later than 01.Oct.2016 11:59 PM CET

About KTH and Science for Life Laboratory:

KTH Royal Institute of Technology in Stockholm (www.kth.se) is 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. The position will be formally placed with the department for Computational Science and Technology (CST) at KTH (https://www.kth.se/en/csc/forskning/cst), but work will be carried out at the Science for Life Laboratory (www.scilifelab.se).

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.

 

Other details:

Type of employment: Temporary position longer than 6 months
Contract type: Full time
First day of employment: According to agreement
Salary: Monthly salary
Number of positions: 1
Working hours: 100%
City: Stockholm
County: Stockholms län
Country: Sweden
Reference number: D-2017-0457

Contact:

Maria Engman / HR Administrator, maengm@kth.se
Kevin Smith, Assistant Professor, ksmith@kth.se