PhD fellowship in Fine-grained Analysis in Brain Imaging, Pioneer Centre for AI
Pioneer Centre for AI, Department of Computer Science, Faculty of Science, University of Copenhagen
The Pioneer Centre for Artificial Intelligence at the Department of Computer Science (DIKU) invites applications for a PhD fellowship in Fine-grained Analysis (FG).
The Pioneer Centre for AI is a multi-university cooperation focusing on fundamental research, and within an interdisciplinary framework, contributing to solving society’s greatest challenges. Hosted by the University of Copenhagen’s Department of Computer Science, cooperating institutions, Denmark’s Technical University, IT University of Copenhagen, Aalborg University, and Aarhus University co-lead the efforts.
Start date is 1 January 2024 or as soon as possible thereafter.
FG: Brain lesion segmentation and characterization in the wild using deep learning
We are seeking a candidate with a strong passion for applied mathematics, machine learning, deep learning, and medical image analysis. The project is centered around the identification and characterization of brain lesions such as white matter hyperintensities within MRI scans. Our goal is to devise robust machine-learning techniques, yielding nuanced insights from clinical data collected in uncontrolled scenarios to help with brain disease diagnosis. Our emphasis lies in establishing the robustness of these methods across various challenges including variations in scanner vendors, field strengths, software, quality, and protocols, while working with heterogeneous data encompassing natural variations in comorbidities and demographics. This study will not only delve into well-established deep learning principles but will also explore innovative avenues based on information theory, active learning, and transfer learning, among other things.
Who are we looking for?
We are looking for a candidate with a curious mind-set and a strong interest in fundamental research questions described in the project.
The Department of Computer Science and the Pioneer Centre for AI - what do we offer?
Employment as a PhD Fellow will be at the Department of Computer Science, Faculty of SCIENCE, University of Copenhagen. The project will be anchored in a research section Pioneer AI at DIKU, as well as at the Pioneer Centre for AI.
PhD students at the Pioneer Centre for AI have extraordinary access to computing resources, to international researchers across many disciplines within computer sciences and other academic areas, as well as courses and events at the centre, and meaningful collaboration with industry, the public sector, and the start-up ecosystem. Centre website: AICentre.dk.
Copenhagen is known among the world’s most livable cities. Whether it’s the bicycle infrastructure, public transporation, green spaces, café and restaurant culture, start-up scene, or cultural and sporting opportunities, the city offers something for everyone.
PhD Fellows, and their accompanying family members, have access to health care and other social benefits. You can read more about employment and the Danish social benefits on the University of Copenhagen’s International Staff Mobility pages.
The PhD programme
The programme is 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.
To be eligible for the regular PhD programme, you must have completed an MSc degree (or obtaining a MSc soon) programme that is 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, e.g. Computer Science, Biomedical Engineering, Computational Physics, Applied Mathematics, Computer and Electrical Engineering, or any relevant degrees with training in Machine Learning, Deep Learning, Artificial Intelligence, and Data Science.
For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database. Note that not all programmes are listed in these databases, so don’t hesitate to ask, if you have questions about your eligibility.
Terms of employment
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.
Terms of appointment and payment accord to the agreement between the Danish Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State. The position is covered by the Protocol on Job Structure.
Responsibilities during the PhD programme:
- Carry through an independent research project under supervision
- Complete PhD courses corresponding to approx. 30 ECTS / ½ FTE
- Participate in active research environments, including a stay at another research institution, preferably abroad
- Teaching and knowledge dissemination activities
- Write scientific papers aimed at high-impact journals
- Write and defend a PhD thesis on the basis of your project
We are looking for the following qualifications:
- Educational and/or professional qualifications relevant to the PhD project
- Relevant publications, if any
- Relevant work experience
- Other relevant professional activities
- Strong motivation for doctoral studies; possessing the ability to work independently, and be creative in problem-solving
- Good English language skills, both oral and written
Application and Assessment Procedure
Your application including all attachments (PDF) must be in English and submitted electronically by clicking APPLY NOW below.
- Motivated letter of application (max. two pages)
- Curriculum vitae including information about your education, experience, language skills and other skills relevant for the position
- Original diplomas for Bachelor of Science or Master of Science and transcript of records in the original language, including an authorized English translation if issued in another language than English or Danish. If the degree is not completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is acceptable.
- Publication list (if relevant)
The deadline for applications is 15 October 2023, at 23:59 CET.
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 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/.
Interviews with selected candidates are expected to be held in November 2023.
Questions about the Pioneer Centre for AI, please contact Michelle Cumming Løkkegaard, email@example.com.
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.