3 PhD fellowships in applied Machine Learning, Information Retrieval and Natural Language Processing

The Information Retrieval Lab of the Department of Computer Science at the University of Copenhagen (DIKU) is offering three fully funded PhD Fellowships in applied Machine Learning, Information Retrieval, and Natural Language Processing, commencing 1 September 2022 or as soon as possible thereafter.

Our group and research - and what do we offer?

The fellows will join the Information Retrieval Lab at the Machine Learning Section at DIKU . The Machine Learning section is among the leading research environments in Artificial Intelligence and Web & Information Retrieval in Europe (in the top 5 for 2020, according to csrankings.org ), with a strong presence at top-tier conferences, continuous collaboration in international & national research networks, and solid synergies with big tech, small tech, and industry. The Machine Learning section consists of a vibrant selection of approximately 65 talented researchers (40 of whom are PhD and postdoctoral fellows) from around the world with a diverse set of backgrounds and a common incessant scientific curiosity and openness to innovation. Moreover, DIKU is internationally leading within Natural Language Processing (ranked 2nd in Europe for the last 5 years, according to CSRankings). The NLP section has a broad portfolio of research, including investigating methods to automatically process, understand, and generate text, with applications including automatic fact-checking, machine translation, question answering, and visually grounded NLP.

The fellows will conduct research, having as starting point the following broad research areas:

• a fully-funded PhD in interpretability of applied machine learning;
• a fully-funded PhD in overparameterization and generalizability in deep neural architectures;
• a fully-funded PhD in web & information retrieval;

Supervisors are Christina Lioma, Tuukka Ruotsalo and Maria Maistro.

Questions

For more information, please contact Professor Christina Lioma, [email protected] , or Associate Professor Tuukka Ruotsalo, [email protected] .

The University of Copenhagen

The University of Copenhagen was founded in 1479 and is the oldest and largest institution of research and education in Denmark. It is a member of the International Alliance of Research Universities, alongside the Universities of Cambridge, Oxford and Yale, and has produced 9 Nobel prize winners . Various academic rankings see the University of Copenhagen as one of the top leading institutions in Europe and the world , and its study programs meet the most stringent international standards for higher education based on Standards and Guidelines for Quality Assurances in the European Higher Education Area and the Danish Accreditation Institution guidelines. 

Life in Copenhagen, Denmark           
International surveys repeatedly rank Denmark among the world’s happiest countries , with high level of social and gender equality, community spirit, and a strong sense of common responsibility for social welfare. Copenhagen is the capital of Denmark, buzzing with culture, sustainable living, modern architecture, royal history, and a mouthwatering restaurant scene.

Who are we looking for?

We are looking for candidates with a MSc degree in a subject relevant for the research area. The successful candidate is expected to have strong grades in Machine Learning and/or Information Retrieval and/or Natural Language Processing. Successful candidates should have a preliminary research record as witnessed by a master thesis or publications in the area.

The PhD programme

Depending of your level of education, you can undertake the PhD programme as either:

Option A: A three year full-time study within the framework of the regular PhD programme (5+3 scheme), if you already have an education equivalent to a relevant Danish master’s degree.

Option B: An up to five year full-time study programme within the framework of the integrated MSc and PhD programme (the 3+5 scheme), if you do not have an education equivalent to a relevant Danish master´s degree – but you have an education equivalent to a Danish bachelors´s degree.

********************************************************************************

Option A: Getting into a position on the regular PhD programme

Qualifications needed for the regular programme 
To be eligible for the regular PhD programme, you must have completed a degree programme, equivalent to a Danish master’s degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the project. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database .

Terms of employment in the regular programme   
Employment as PhD fellow is full time and for maximum 3 years.

Employment is conditional upon your successful enrolment as a PhD student at the PhD School at the Faculty of SCIENCE, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant.

The terms of employment and salary are in accordance to the agreement between the Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State (AC). The position is covered by the Protocol on Job Structure.

Option B: Getting into a position on the integrated MSc and PhD programme

Qualifications needed for the integrated MSc and PhD programme

If you do not have an education equivalent to a relevant Danish master´s degree, you might be qualified for the integrated MSc and PhD programme, if you have an education equivalent to a relevant Danish bachelor´s degree. Here you can find out, if that is relevant for you: General assessments for specific countries and Assessment database .  

Terms of the integrated programme  
To be eligible for the integrated scholarship, you are (or are eligible to be) enrolled at one of the faculty’s master programmes in Computer Science.

Students on the integrated programme will enroll as PhD students simultaneously with completing their enrollment in this MSc degree programme.

The duration of the integrated programme is up to five years, and depends on the amount of credits that you have passed on your MSc programme. For further information about the study programme, please see: www.science.ku.dk/phd , “Study Structures”.

Until the MSc degree is obtained, (when exactly two years of the full 3+5 programme remains), the grant will be paid partly in the form of 48 state education grant portions (in Danish: “SU-klip”) plus salary for work (teaching, supervision etc.) totalling a workload of at least 150 working hours per year.
A PhD grant portion is currently (2022) DKK 6,397 before tax.

When you have obtainedtheMSc degree, you will transfer to the salary-earning part of the scholarship for a period of two years. At that point, the terms of employment and payment will be according to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State (AC). The position is covered by the Protocol on Job Structure.

Responsibilities and tasks in both PhD programmes

• Complete and pass the MSc education in accordance with the curriculum of the MSc programme

 (ONLY when you are attending the integrated MSc and PhD programme)

• Carry through an independent research project under supervision

• Complete PhD courses corresponding to approx. 30 ECTS / ½ FTE
• Carry out limited dissemination and teaching activities
• Participate in active research environments, including a stay at another research institution, preferably abroad
• Write scientific papers aimed at high-impact venues
• Write and defend a PhD thesis on the basis of your project

We are looking for the following qualifications:

• Professional qualifications relevant to the PhD project
• Relevant publications are desirable, but not necessary
• Relevant work experience is desirable, but not necessary
• Curious mind-set with a strong interest in Machine Learning and/or Information Retrieval and/or a combination of these with Human-Centered Computing
• Proficiency in the English language

***************************************************************************

Application and Assessment Procedure

 Your application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.

Please include: 

Application deadline:

The deadline for applications is 19 May 2022, 23:59 GMT +2.

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.

The further process         
After the deadline, a number of applicants will be selected for academic assessment by an unbiased expert assessor. You are notified, whether you will be passed for assessment.

The assessor will assess the qualifications and experience of the shortlisted applicants with respect to the above mentioned research area, techniques, skills and other requirements. The assessor will conclude whether each applicant is qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/ .

Questions
For specific information about the PhD fellowship, please contact the principal supervisor.

General information about PhD study at the Faculty of SCIENCE is available at the PhD School’s website: https://www.science.ku.dk/phd/ .

The University of Copenhagen wishes to reflect the surrounding community and invites all regardless of personal background to apply for the position. 

Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.