The Department of Health Technology at the Technical University of Denmark (DTU Health Tech) is looking for a Ph.D. candidate in data science for digital phenotyping. The purpose of this project is to research, design, implement, and test a workflow pipeline for the training of machine learning prediction algorithms for digital biomarkers from mobile and wearable technology.
You will join the Digital Health section of DTU Health Tech. We are a multi-disciplinary team of biomedical engineers, computer scientists, and UX researchers who research digital technologies for health, healthcare, and life science, in order to improve healthcare delivery and make healthcare more personalized and precise. We have an extensive research record within data science and digital phenotyping, and you will join a team of senior researchers and other Ph.D. students. You will also work closely with medical doctors at the Copenhagen University Hospital who will provide clinical supervision.
Responsibilities and qualifications
Your research will focus on establishing an end-to-end pipeline for data science in digital phenotyping with a special focus on cardiology, neurology, and mental health. This pipeline will consist of three main parts: (i) collection of mobile, wearable, and behavioral data from patients, (ii) ground-truth annotation from clinicians, and (iii) a self-optimizing and extensible data science analysis engine containing models for identification of digital biomarkers and prediction of clinically relevant events. The primary focus is on the overall software architecture and distributed system design of the pipeline, secondary on the user experience (UX) design of the use of digital biomarkers both by patients and clinicians, and tertiary on the design of data science methods. From an empirical and practical point-of-view, the research will be based on, and extend, the Copenhagen Research Platform (CARP).
This position requires skills in software engineering, mobile sensing, UX design, and health data science, including software development, mobile programming, sensor integration, distributed computing, and data processing using modern AI- and ML-based tools. Furthermore, a structured approach to research and strong communication skills in English in written and oral dissemination is core. Finally, since you will be spending time with a clinical team at the hospital, good collaborative skills and an understanding of clinical work are important.
From an academic point of view, 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 in addition to a bachelor’s degree (180 ECTS points).
Ideally, your master's degree should be in computer science, computer engineering, or biomedical engineering with a focus on software engineering and data science.
More specifically you should have most of the following qualifications:
- Strong theoretical and practical background in software engineering, software architecture, distributed computing, data science, and human-computer interaction.
- Experience in mobile sensing, ubiquitous computing, and wearable devices.
- Experience in data science methods, incl. machine/deep learning algorithms, especially in biomedical signal processing applications.
- Strong mastery of programming languages like Python, Java, Kotlin, Dart, Swift, or similar.
- Strong communication skills in English – both in writing and orally.
- Knowledge of clinical work, e.g., in hospitals or clinics.
The language of communication at DTU is English.
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.
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 according to mutual agreement. The position is a full-time position.
You can read more about career paths at DTU here.
Further information
If you want to know more, please contact the main supervisor directly – Jakob E. Bardram at [Email Address Removed].
Read more about:
· Department of Health Technology
· The Digital Health section
· The Ph.D. School at DTU Health Tech
· mCardia – an example of our work in cardiology
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 Ph.D. at DTU.
Application procedure
Your complete online application must be submitted no later than 11 June 2023 (Danish time). Apply online here: PhD Scholarship in Data Science Pipeline for Digital Phenotyping.
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 an official description of the grading scale
- Links to, or copies of any research papers you may have been part of
- Link to a code portfolio stored in an online repository like GitHub
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.
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