DrJan-Philipp Cieslik

Honorary Research Associate

Department of Surgery & Cancer - Faculty of Medicine

  • Honorary Research Associate
    Department of Surgery & Cancer - Faculty of Medicine

RESEARCH

  • Translational Oncology & Precision Medicine: Mechanisms of therapy resistance in breast and prostate cancer, circulating tumor cells (CTCs), and cell-free DNA (cfDNA) as biomarkers.
  • Single-Cell Technologies & Optical Tweezers: Development and application of AI-guided platforms for autonomous single-cell isolation and analysis.
  • Computational Cancer Biology: Machine learning and bioinformatics approaches for integrating multi-omics data into clinical decision-making.
  • Clinical Trial Translation: Evaluation of therapeutic efficacy and biomarker dynamics in multicenter oncology trials.

GRANTS

  • GRANT
    Clinic Edge
    Medical Deanery and E-Learning Development Fund, Heinrich Heine University Düsseldorf1 Jan 2024 - 31 Dec 2026
    €168,429 in funding for project work and to support student research assistants. Development of a browser-based simulation platform to train medical students in clinical reasoning and the use of a hospital information system (HIS). Unlike existing linear case-based simulators, the platform presents randomized, realistic clinical cases in a fully functional HIS environment. Students can record diagnoses, order investigations, document findings, and prescribe medications using realistic workflows that mirror daily clinical practice. The system emphasizes independent problem-solving, critical thinking, and practical application of clinical knowledge. This project aligns with the German National Competency-Based Catalogue of Learning Objectives in Medicine (NKLM 2.0), particularly in training students to manage patient care interfaces, utilize medical documentation, and apply quality management concepts in clinical workflows.
  • GRANT
    Cancer Informatics: Preparing Students for the Clinic and Research of Tomorrow.
    E-Learning Development Fund of the Heinrich Heine University1 Jan 2022 - 31 Dec 2024
    Allocated €19,521 for student research assistants to establish and support the project. Developed an open-source, modular e-learning platform introducing medical and biology students without prior programming experience to computational oncology. Modules combine texts, recorded lectures, and interactive, case-based exercises with automated feedback, teaching fundamental data handling, R and Python programming, and practical in silico research skills. Materials can be used independently or in elective courses and are freely accessible for learning and contribution.