DTU Tenure Track Assistant Professor in Explainable AI Bioinformatics - DTU Health Tech

If you are at the start of your career as scientist in Bioinformatics and you are looking for the best possible foundation for getting established in the academic world, the possibility is right here in front of you. At the Bioinformatics Section at DTU Health Tech you will break new ground at the absolute forefront of what is possible in explainable AI (Artificial Intelligence) Bioinformatics for health. 
The Bioinformatics section at the Department of Health Technology has its main research and teaching activities in bio-medical and bio-technological informatics, immunoinformatics, cancer bioinformatics, metagenomics, epidemiology, integrative systems biology and machine learning. Our research at DTU Bioinformatics is focused on bioinformatics and computational analyses of large amounts of data generated within biological, biomedical and biotechnological and life sciences area. The section has extended international and national collaborations including industrial and clinical partners. The section for Bioinformatics has been playing a key role in developing the field of health bioinformatics.

The successful candidate will have the opportunity to do research in the development of methods that are explainable, interpretable, and understandable to humans for predicting health outcomes which may be dependent on nonlinear interactions such as epistatic mechanisms. Prediction of human health may be based on different types of genomic data (human genome, metagenome, Infectious agents) as well as other types of data including expression data, immune profiling, metabolome data, and general health data (e.g. from electronic patient journals, or other registers). All these data may be used as input to bioinformatics software that is (part of) medical devices that can be used for developing tailored medical approaches for disease diagnosis and prevention. The research will help implement, validate, benchmark, and improve how bioinformatics is used in medical devices. The successful candidate is expected to contribute to this strong position through front line research and innovation within the field. In particular, the candidate would have demonstrated expertise in bioinformatic analyses of different -omics data (such as genomics, proteomics, gene expression etc.), use of ML (Machine Learning)/AI and have a solid biological background for understanding the field that these methods will be used in. A strong ability to work in close collaboration with experimentalists and clinicians will be also critical. In addition, familiarity with projects for software development for bioinformatics will be highly beneficial.
The position is part of the NNF funded Inter-CeBIL – International Collaborative Biomedical Innovation & Law Program center, headed by Copenhagen Law School which aims to do strengthen the Danish and international research environment within biomedical innovation by delivering research on legal, ethical, and socio-economic aspects of health and life science research in Denmark and globally in the areas of Advanced medical computing, Artificial Intelligence (AI) and Quantum Technologies (QT), Pandemic preparedness and Anti-Microbial Resistance (AMR), and Sustainable innovation.The role of DTU in the project is to explore the possibilities of developing a  of an AI basis for making interpretable and understandable medical devices for prediction of disease outcome based on genomic and other health data. 

Responsibilities and qualifications
Your overall focus will be to strengthen the department’s competences within Explainable AI, in the area of using omics data for prediction of health. You will work with nearby colleagues, and with both academic and industrial partners in Denmark as well as abroad. Your primary tasks will be to:

• Research in the development of methods that are explainable AI methods, that are legally acceptable for use in the health system.
• Develop teaching in the area of using AI and bioinformatics to predict health outcomes, based on different omics data, and other health data.
• Teach and supervise BSc and MSc student projects, and be co-supervisor for PhD students

The successful candidate is expected to have 2-4 years Post Doc experience in research in bioinformatics and AI related to health. You must be responsible for the teaching of courses. DTU employs two working languages: Danish and English. You are expected to be fluent in at least one of these languages, and in time are expected to master both. As formal qualification you must hold a PhD degree (or equivalent).

You will be assessed against the responsibilities and qualifications stated above and the following general criteria:

• Experience and quality of teaching 
• Research experience 
• Research vision and potential
• International impact and experience 
• Societal impact
• Innovativeness, including commercialization and collaboration with industry
• Leadership, collaboration, and interdisciplinary skills
• Communication skills

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 part of DTU’s Tenure Track program. Read more about the program and the recruitment process here.
You can read more about career paths at DTU here.

Further information 
Further information may be obtained from Professor Ole Lund, olund@dtu.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 28 December 2023 (23:59 Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• Application (cover letter)
• Vision for teaching and research for the tenure track period 
• CV including employment history, list of publications, H-index and ORCID (see http://orcid.org/)
• Teaching portfolio including documentation of teaching experience 
• Academic Diplomas (MSc/PhD)

Applications received after the deadline will not be considered.
All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.

DTU Health Tech engages in research, education, and innovation base on technical and natural science for the healthcare sector. The Healthcare sector is a globally expanding market with demands for the most advanced technological solutions. DTU Health Tech creates the foundation for companies to develop new and innovative services and products which benefit people and create value for society. DTU Health Tech’s expertise spans from imaging and biosensor techniques, across digital health and biological modelling, to biopharma technologies. The department has a scientific staff of about 210 persons, 140 PhD students and a technical/administrative support staff of about 160 persons, of which a large majority contributes to our research infrastructure and related commercial activities.

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 mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.

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