Associate Professor in Statistical Machine Learning for Neuroimaging (part-time)

The position is available from January 1, 2021 or according to mutual agreement. The Section for Cognitive Systems 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, behaviour – and the opportunities these signals offer for modelling 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. Modern neuroimaging techniques generate large amounts of complex data and sophisticated machine learning methodology is needed to process and analyse these types of data in efforts to develop potential biomarkers and improve our understanding of the human brain. To strengthen the Department’s teaching and research in this field, we are seeking an Associate Professor in statistical machine learning for neuroimaging.

Responsibilities and tasks
You will advance interdisciplinary research on analysis of functional neuroimaging data, working at the intersection between cognitive science, physics, health, and computer science. You will contribute to develop novel methods for analysis of neuroimaging data with special emphasis on methods for uncertainty quantification, active learning and causal inference.

The successful candidate is supposed to participate and develop departmental teaching on machine learning, covering Bachelor-, Master- and PhD-level courses, and participate in the supervision of graduate students.
The successful applicant will collaborate with DTU Compute faculty to develop innovative research and teaching and contribute to educational activities in the health sector.

Qualifications
Candidates must:

• hold a PhD degree (or equivalent), as well as academic qualifications equivalent to those obtained by holding an assistant professorship
• document didactic/pedagogic training  
• Hold a PhD in Applied Mathematics, Physics, Computer Science, Cognitive Science or related field.
• Have an outstanding research record in machine learning and neuroimaging, as demonstrated by journal publications at the highest international level.
• Have demonstrated experience with analysis of neuroimaging data and collaboration within the health sciences.
• Have experience with teaching and educational activities within both machine learning and neuroimaging.
• Have strong motivation for interdisciplinary research.
• Be experienced in collaboration between health science institutions and universities

Assessment
In the assessment of the candidates, consideration will be given to:

• Experience and quality of teaching
• Research impact and experience, funding track record, and research vision
• Societal impact
• Documented innovation activities, including commercialization and collaboration with industry
• International impact and experience
• Leadership potential and collaboration
• Communication skills
• Experience with collaboration between health science institutions and universities

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 terms of employment
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 position is a part-time appointment (17.5 hours/week) available from January 1, 2021 or according to mutual agreement. You can read more about career paths at DTU here .

Further information
Further information may be obtained from Head of Section, Lars Kai Hansen, tel.: +45 4525 3889.
You can read more about DTU Compute at www.compute.dtu.dk .

Application procedure
Please submit your online application no later than 25 October 2020 (local time). Apply online via "Ansøg"
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:

• Application (cover letter)
• CV
• Teaching and research statement, with a focus on the “Assessment” bullet points listed above
• Documentation of previous teaching and research, as related to the “Assessment” bullet points listed above
• List of publications
• H-index, and ORCID (see e.g. http://orcid.org/ )
• Diploma (MSc/PhD)

Applications and enclosures received after the deadline will not be considered.
All qualified 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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