Ph.D. in Machine Learning for Digital Biomarker in Outpatient Geriatric Psychiatry 100 %
University Hospital of Old Age Psychiatry and Psychotherapy
Start of employment: 01.05.2024 or by agreement
Employment is fixed term for 3 years.
Our research focuses on healthy ageing and neurodegenerative and mental illness in people over the age of 65. Our expertise is drawn from geriatric psychiatry, neuropsychology, clinical psychology and computer science.
As part of this research, you will be significantly involved in designing, implementing and analysing a study on developing digital biomarkers using passive sensing. Your role will include the design of a comprehensive data analysis pipeline based on one or more available data streams. You will be responsible for pre-processing and analysing the data and developing machine-learning models to identify and validate digital biomarkers. This role requires a deep understanding of data-driven research methods and the ability to interpret complex data sets and develop innovative solutions to geriatric psychiatry and psychology challenges.
Start of employment: 01.05.2024 or by agreement
Employment is fixed term for 3 years.
Our research focuses on healthy ageing and neurodegenerative and mental illness in people over the age of 65. Our expertise is drawn from geriatric psychiatry, neuropsychology, clinical psychology and computer science.
As part of this research, you will be significantly involved in designing, implementing and analysing a study on developing digital biomarkers using passive sensing. Your role will include the design of a comprehensive data analysis pipeline based on one or more available data streams. You will be responsible for pre-processing and analysing the data and developing machine-learning models to identify and validate digital biomarkers. This role requires a deep understanding of data-driven research methods and the ability to interpret complex data sets and develop innovative solutions to geriatric psychiatry and psychology challenges.
Ph.D. in Machine Learning for Digital Biomarker in Outpatient Geriatric Psychiatry
Tasks
- Conceptual development, implementation and evaluation of a longitudinal passive sensing study in outpatient geriatric psychiatry.
- Investigation of the usefulness of passive sensing as a complementary or alternative measurement instrument for predicting symptoms, diagnoses and therapy success.
- Development of a feedback platform for patients and therapists, including a possible automated transcription of the therapeutic conversation.
- Communication and publication of research results (specialist journals, conference papers), possibly support for testing (inpatient and outpatient) and teaching.
Requirements
- Completed university degree in psychology, computer science, medical informatics or a comparable degree with a Swiss GPA of 5.0, a German GPA of 2.0, or similar GPA based on the grading system
- Interest in geriatric psychiatry/psychology, the associated challenges and possible digital solutions in response to these challenges
- Prior knowledge and recognisable interest in the areas of data processing, feature engineering (e.g. OpenSmile, Praat), machine learning and statistical programming skills (R or Python)
- Strong interest in research, scientific writing and an academic career
- Very good written and spoken English; knowledge of German is an advantage
We offer
- Varied, multifaceted, and challenging tasks at the interface between medical, psychological and technical research
- An agile and committed team with clinical and technical expertise
- A large degree of creative freedom
- Very good academic career development opportunities
Application and contact
For subject-specific questions and information about the position, please contact Dr. Gisbert W. Teepe (Write an email).
About the company
