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PhD project in Deep Learning for Image-Based Quality Assessment

Danmarks Tekniske Universitet (DTU)



Frist 20. april 2021

DTU

Compute’s

Section

for Cognitive

Systems

invites

applications

for a 3-year

PhD

position 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.

The

project

is

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 the

Section

for Cognitive Systems. The section is

a lively

and

research

oriented

group of scientists and

support staff

with

a shared

interest

in

information

processing

in

man

and

computer,

and

a particular

focus

on the

signals

they exchange

- audio,

imagery, behavior

– and

the

opportunities

these

signals

offer

for modeling and

engineering

of cognitive

systems.

The

Section

is

working

actively

to

keep

a healthy

work-life

balance

and

we are

aware

of the

challenges facing

young families

in

academia.

Working

at

DTU

provides

much

flexibility

and

families

in

Denmark enjoy

a highly

developed

and

affordable

childcare

system.

Responsibilities and qualifications
Are

you interested

in

developing

new

deep

learning methods for understanding of visual data?

Then

you might

be our new

PhD

student.

Y

our tasks will be to

  • Develop
  • image data.

    deep learning methods for analysis of

    implement

    and

  • 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
  • machine learning conferences, such NeurIPS, ICML, ICLR, CVPR etc.

    top

    in

    research

    your

  • Develop,
  • the wider machine learning community.

    to

    available

    research

    your

    make

    to

    software

    source

    open

    publish

    and

    document,

  • Contribute to the productive
  • project’s needs.

    the

    aligned with

    is

    your research

    that

    FOSS, DIKU and DTU Compute and by your presence ensure

    collaboration between

We

expect

that

you are

highly

motivated

and

self-driven and

strive

for excellence.

Qualifications

Candidates

should

have

a two-year

master's

degree

(120 ECTS

points)

or a similar

degree

with

an

academic level

equivalent

to

a two-year

master's

degree.

The

master

degree

should

be in

engineering, computational

science,

applied

mathematics

or equivalent.

Preference

will

be given

to

candidates

who can

document

experience

in

deep

learning, solid coding skills and research experience.

G

ood command

of the

English language

is

essential.

Approval

and

Enrolment

The

scholarship

for the

PhD degree

is

subject

to

academic approval,

and

the

candidate

will

be enrolled

in

the

DTU

Compute

PhD School

Program.

For information

about

the

general

requirements

for enrolment

and

the

general

planning

of the

PhD

study program,

please

see

the

DTU

PhD

Guide

.

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 20

April 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.

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Danmarks Tekniske Universitet (DTU) - hurtigt overblik


Danmarks Tekniske Universitet (DTU)
Danmarks Tekniske Universitet (DTU)
DTU er et teknisk eliteuniversitet med international rækkevidde og standard. Vores mission er at udvikle og nyttiggøre naturvidenskab og teknisk videnskab til gavn for samfundet. 11.200 studerende uddanner sig her til fremtiden, og 6.000 medarbejdere har hver dag fokus på uddannelse, forskning, myndighedsrådgivning og innovation, som bidrager til øget vækst og velfærd.

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