PhD project in Deep Learning for Image-Based Quality Assessment

Updated: 2 months ago

DTUCompute’sSectionfor CognitiveSystemsinvitesapplications for a 3-yearPhDposition starting summer 2021.

The project will carried out in collaboration with FOSS, a Danish company producing end-to-end solutions that secure and improve food quality. FOSS analysis instruments refine measurements into information management that enables businesses to run intelligent data-driven productions with less waste and bigger yields. Theprojectis funded by DIREC - Digital Research Center Denmark and also involves scientists at Department of Computer Science at University of Copenhagen (DIKU).

The research aim of the project is the development of AI methods and tools that enable industry to develop new solutions for automated image-based quality assessment.

The main part of the PhD study will take place in theSectionfor Cognitive Systems. The section is a livelyandresearchoriented group of scientists and support staffwith a sharedinterestininformationprocessinginmanandcomputer,and a particularfocus on thesignalsthey exchange - audio,imagery, behaviorandtheopportunitiesthesesignalsoffer for modeling andengineering of cognitivesystems.TheSectionisworkingactivelytokeep a healthywork-lifebalanceand we areaware of thechallenges facing young familiesinacademia.WorkingatDTUprovidesmuchflexibilityandfamiliesinDenmark enjoy a highlydevelopedandaffordablechildcaresystem.

Responsibilities and qualifications
Areyou interestedindevelopingnewdeeplearning methods for understanding of visual data?Then you might be our newPhDstudent.Your tasks will be to

  • Developandimplement deep learning methods for analysis of image data.
  • Motivated by the FOSS data challenges you will research methods for improved deep learning in complex, real world settings based on weakly supervised methods, including semi-supervised and self-supervised learning. Other topics of interest include the detection of out-of-distribution events, explainability and active learning.
  • Disseminate yourresearchin top machine learning conferences, such NeurIPS, ICML, ICLR, CVPR etc.
  • Develop,document,andpublishopensourcesoftwaretomakeyourresearchavailabletothe wider machine learning community.
  • Contribute to the productivecollaboration between FOSS, DIKU and DTU Compute and by your presence ensurethat your researchisaligned with the project’s needs.

Weexpectthatyou are highly motivatedandself-driven andstrive for excellence.

Qualifications
Candidatesshouldhavea two-yearmaster'sdegree (120 ECTSpoints) or a similardegreewithanacademic levelequivalentto a two-yearmaster'sdegree.Themasterdegreeshould be inengineering, computationalscience,appliedmathematics or equivalent.

Preferencewillbe giventocandidates who candocumentexperienceindeeplearning, solid coding skills and research experience.Good command of theEnglish languageisessential.

ApprovalandEnrolment
Thescholarshipfor the PhD degreeissubjecttoacademic approval,andthecandidatewill be enrolledintheDTUCompute PhD SchoolProgram. For informationaboutthegeneralrequirements for enrolmentandthegeneralplanning of thePhDstudy program,pleaseseetheDTUPhDGuide

Assessment
The assessment of the applicants will be made by Lars Kai Hansen, DTU Compute, Thomas Nikolajsen, FOSS and Kim Steenstrup Pedersen, DIKU. 

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

You can read more about career paths at DTU here .

Further information
Further information may be obtained from Lars Kai Hansen, Section for Cognitive Systems, DTU Compute, email: lkai@dtu.dk and Thomas Nikolajsen, tel.: +45 6021 6989. 

You can read more about DTU Compute at www.compute.dtu.dk , DIREC at direc.dk, FOSS at www.fossanalytics.com and more about DIKU at www.di.ku.dk . 

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark .

Application procedure
Your complete online application must be submitted no later than 20April 2021 (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma
  • Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here )

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Compute
DTU Compute is a unique and internationally recognized academic environment spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard—producing new knowledge and technology-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), internet of things (IoT), smart and secure societies, smart manufacturing, and life science.

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 12,000 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup and in Sisimiut in Greenland.


View or Apply

Similar Positions