PhD scholarship in Explainable AI and Bioinformatics for Health

Are you interested in becoming a bioinformatics PhD student working to develop methods for explainable AI (Artificial Intelligence) and Bioinformatics for health? Then this is the position for you. You will join the ongoing efforts of researchers at the Department of Health Technology (DTU Health Tech) at the Technical University of Denmark. 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. You will be joining the group of Health Bioinformatics and Personalised Medicine in the Section for Bioinformatics. We combine knowledge of biology with informatics to study questions that are often relevant to human health but equally often of a fundamental nature. The research challenges we address are related to handling and interpretation of these large-scale heterogeneous data, and our research strategy is focused on developing tools to address these challenges and apply them to data sets to generate biological insights. Responsibilities and qualifications
You will work on analyzing and integrating multiple omics data modalities, ranging from gene expression profiling and immunophenotyping to tissue images. You 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. Prediction of human health may be based on different types of genomic data as well as other types of data including expression data, immune profiling, metabolome data, imaging data and general health data (e.g. from electronic patient journals, or other registers). Classical genetic studies often use polygenic risk scores (PRS), which sum up the effect over the strongest associated variants to predict an individual's phenotype. However, these linear methods have been shown to have limited diagnostic value, which has spawned an interest in more complex models for calculating polygenic risks. This project will explore the possibility of integrating the benefits of linear methods with deep neural networks, which can learn interactions and non-linear relationships. A central goal of the project is to develop explainable machine learning models that allow insight into the interaction between genetics and other types of data 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. You would have an educational background of bioinformatic analyses of different -omics data (such as genomics, proteomics, gene expression etc.), and imaging data, 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. The following requirements must be met by the successful candidate:

• Experience working with bioinformatics
• Strong programming skills

You must 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. Approval and Enrolment 
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education .  Assessment
The assessment of the applicants will be made by Professor Ole Lund and Carolina Barra Quaglia.  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. Starting date is as soon as possible. The position is a full-time position. You can read more about career paths at DTU here Further information 
Further information may be obtained from Professor Ole Lund, . You can read more about the DTU Health Tech and the Section for Bioinformatics at  and  If you are applying from abroad, you may find useful information on working in Denmark and at DTU at  DTU – Moving to Denmark . Furthermore, you have the option of joining our monthly free seminar “ PhD relocation to Denmark and startup “Zoom” seminar ” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU. Application procedure 
Your complete online application must be submitted no later than 25 June 2024 (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:

• A letter motivating the application (cover letter)
• Curriculum vitae 
• Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
• Letters of recommendation (not mandatory)

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it. Applications received after the deadline will not be considered. All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply. With a vision to improve health and quality of life through technology, DTU Health Tech engages in research, education, and innovation based on technical and natural science. We educate tomorrow’s health tech engineers and create the foundation for new and innovative services and technologies for the globally expanding healthcare sector with its demands for the most advanced technological solutions. DTU Health Tech’s expertise can be described through five overall research areas: Diagnostic Imaging, Digital Health, Personalised Therapy, Precision Diagnostics, and Sensory and Neural Technology. Our technologies and solutions are developed with the aim of benefiting people and creating value for society. The department has a scientific staff of about 210 persons, 140 PhD Students, and a technical/administrative support staff of about 100 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 13,400 students and 5,800 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.