Doctoral students in Natural Language Processing / Machine Learning

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 architecture, industrial management, urban planning, history and philosophy.

The Division of Software and Computer Systems within the Department of Computer Science of the School of Electrical Engineering and Computer Science, KTH is looking for excellent candidates for two PhD student positions in the intersection of the following areas: natural language processing, natural-language understanding, deep learning (DL). 

The advertised positions are within the project “ALEC2: Adaptive Level of Effective and Continuous Care to common mental health disorders” that aims at development of AVA (Automated Vigilance Assistant), an AI-supported system for online cognitive behavioral therapy to patients with common mental health disorders. AVA will make use of AI technologies, namely NLP, NLU and DL, to automatically diagnose, predict and monitor mental health conditions, to support patients towards full recovery.

The doctoral students will contribute to development of the AVA system with AI modules and a conversational AI to interview patients.

Preliminary starting date is Oct 15.

Third-cycle subject:Information and Communication Technology

Supervision: The doctoral student will be supervised by Professor Vladimir Vlassov.

• International research environment in collaboration with industries/prominent universities all over the world Read more
• A workplace with many employee benefits, monthly salary according to KTH’s Doctoral student salary agreement
• A postgraduate education at institution active and supportive in matters pertaining to working conditions, gender equality,diversity as well as study environment
• Our research group offers a friendly working environment and the main language used is English. We perform foundational and systems research in areas of Deep Learning, big data analytics, data intensive computing, stream processing, distributed systems, Cloud computing and autonomic computing
• relocate and be settled in Sweden and at KTH .

To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance)  applicant must have basic eligibility in accordance with either of the following:

• passed a second cycle degree (for example a master's degree)
• completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
• acquired, in some other way within or outside the country, substantially equivalent knowledge

The applicant must have strong academic credentials, including courses on least one of the subjects: NLP, NLU, DL; written and spoken English proficiency. Written and spoken Norwegian or Swedish proficiency is beneficial. Good to have work experience from at least one of the areas: NLP, NLU, DL.

In addition, there is also a mandatory requirement for English equivalent to English B/6, read more here

In order to succeed as doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process candidates will be assessed upon their ability to:

• independently pursue his/her work
• collaborate with others
• have a professional approach 
• analyse and work with complex issues
• Practical problem-solving skills and creativity; motivation for doctoral studies

After the qualification requirements, great emphasis will be placed on personal competency. 

Target degree: Doctoral degree

Only those admitted to postgraduate education may be employed as a doctoral student. Total length of employment may not be longer than what corresponds to full-time doctoral education in four years time. An employed doctoral student can, to a limited extent (maximum 20%), perform certain tasks within their role, e.g. training and administration. A new position as a doctoral student is for a maximum of one year, and then the employment may be renewed for a maximum of two years at a time.

You will find contact information for union representatives on KTH's website

You will find contact information for doctoral section on the section's website

Apply for position and admission through KTH's recruitment system. It is the applicant’s responsibility to ensure that application is complete in accordance with instructions in advertisement.

Applications must be received at the last closing date, midnight CET/CEST (Central European Time/Central European Summer Time)

Applications must include following elements:

• CV including relevant professional experience and knowledge
• Application letter with brief description of why you want to pursue research studies, about what your academic interests are, how they relate to your previous studies and future goals (Maximum 2 pages long)
• Copies of diplomas and grades from previous university studies and certificates of fulfilled language requirements (see above) . Translations into English or Swedish if original document is not issued in one of these languages
• Representative publications or technical reports. For longer documents, please provide a summary (abstract) and web link to the full text

Striving towards gender equality, diversity and equal conditions is both a question of quality for KTH and a given part of our values.

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

Type of employment: Temporary position longer than 6 months
Contract type: Full time
First day of employment: As agreed
Salary: Monthly salary according to KTH's doctoral student salary agreement
Number of positions: 2
Working hours: 100%
City: Stockholm
County: Stockholms län
Country: Sweden
Reference number: J-2021-1905
Contact:

Published: 2021-09-09
Last application date: 2021-09-30