PhD student (d/f/m) Physiological Signal Processing for Clinical Decision Support

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Work time

part-time

Start date

01.11.2026

Employment period

limited

Application deadline

15.09.2026

Deployment location Charité

Campus Charité Mitte

Jobcode

8179

Salary group

E13

Working at Charité

The Institute for AI in Medicine, established at Charité in November 2025, systematically integrates computer science with medicine and the basic sciences. Its portfolio spans fundamental AI research, the development of clinical applications, and their rigorous evaluation in routine healthcare settings. The institute places a strong emphasis on application-oriented research and development. In close collaboration with the Berlin Institute for the Foundations of Learning and Data (BIFOLD), it develops novel AI methods, adapts them to medical use cases, and translates them into clinical practice.

Overview of the position

For the HumAMI project, we are seeking a highly motivated PhD candidate with a strong quantitative and methodological-technical background. The position is particularly suited to candidates who wish to work at the interface of artificial intelligence, biosignals, and clinical research, and who aim to translate technical methods into robust, clinically relevant applications.

Your responsibilities will include:

Conducting a doctoral research project at the interface of artificial intelligence, signal processing, and clinical research

Developing and evaluating AI-based methods for multimodal physiological monitoring and clinical decision support

Processing, synchronizing, assessing the quality of, and analyzing multimodal physiological data

Employing technologies such as remote photoplethysmography (rPPG), radar-based sensing, and other physiological and contextual sensors

Methodological focus on signal processing and machine learning

Contributing to AI-supported clinical decision support systems based on retrieval-augmented generation (RAG) and agent-based approaches

Working in an interdisciplinary team comprising computer scientists, data scientists, and clinicians

Collaborating with academic, clinical, and industrial partners within the HumAMI consortium

The position is offered as a research associate role. In accordance with § 110 (4) sentence 3 of the Berlin Higher Education Act (BerlHG), scientific staff are granted appropriate time during working hours to pursue their own academic qualification.

What we are looking for

Completed university degree (Masters or equivalent) in computer science, data science, artificial intelligence, biomedical engineering, medical informatics, applied mathematics, physics, or a related quantitatively oriented field

Very good programming skills, preferably in Python, along with experience in scientific computing and common libraries for data analysis and machine learning

Solid knowledge of machine learning, statistical data analysis, and quantitative research methods

Experience with time-series data, signal processing, and/or the analysis of biological signals

Experience with physiological signals such as ECG, PPG/rPPG, blood pressure data, or radar-based sensor systems is an advantage

Familiarity with relevant signal-processing concepts, e.g. filtering, segmentation, feature extraction, and signal quality assessment

Experience with temporal alignment of multimodal data, data synchronization, sensor fusion, or related methods is desirable

Experience in the development, validation, and performance evaluation of machine learning models

Familiarity with longitudinal, repeated-m