[SocBiN] Positions in Digital Twins Modeling for drug discovery

[Tang, Jing]

PhD Student or Post-Doc Position in Digital Twins Modelling of Drug Responses for Cancer Patients

Position Title: PhD Student or Post-Doctoral Researcher in Digital Twin Modelling

Location: Faculty of Medicine, University of Helsinki, Finland

Duration: 3 years (full-time)
Application Deadline: March 1, 2025

About the Project:
We are excited to announce an opening position for a PhD student or post-doctoral researcher to join our team working on the cutting-edge EU-funded project DTRIP4H (https://www.dtrip4h.eu/). The project aims to develop digital twin models to predict drug targets and drug responses in cancer patients, enabling personalized treatment strategies and improving patient outcomes.

Position Overview:
The successful candidate will be involved in the development and implementation of digital twin models that simulate and predict drug responses in cancer patients. This interdisciplinary project combines computational modelling, machine learning, and biomedical data analysis to create personalized digital replicas of patients for optimizing cancer therapy.

Key Responsibilities:
- Develop and refine computational models for digital twins of cancer patients.
- Integrate multi-omics data (genomics, transcriptomics, proteomics) and clinical data into the models.
- Apply machine learning and AI techniques to predict drug responses and optimize treatment strategies.
- Collaborate with a multidisciplinary team of cancer researchers, clinicians, and data scientists.
- Publish research findings in high-impact scientific journals and present at international conferences.

Qualifications:
- For PhD Candidates:
  - A Master's degree in Bioinformatics, Computational Biology, Biomedical Engineering, Computer Science, or a related field.
  - Strong background in computational modelling, machine learning, or data analysis.
  - Proficiency in programming languages such as Python, R, or MATLAB.
  - Excellent written and verbal communication skills in English.
  - Prior experience in cancer research or personalized medicine is a plus.

- For Post-Doc Candidates:
  - A PhD in Bioinformatics, Computational Biology, Biomedical Engineering, Computer Science, or a related field.
  - Proven track record of research in computational modeling, machine learning, or biomedical data analysis.
  - Strong publication record in peer-reviewed journals.
  - Experience with multi-omics data integration and analysis.
  - Excellent project management and teamwork skills.

What We Offer:
- A stimulating and collaborative research environment.
- Access to state-of-the-art computational resources and datasets.
- Opportunities for professional development and networking within the EU DTRIP4H consortium.
- Competitive salary and benefits package according to institutional standards.

How to Apply:
Interested candidates should submit the following documents to jing.tang at helsinki.fi<mailto:jing.tang at helsinki.fi> by March 1, 2025:
1. A cover letter outlining your research interests and motivation for applying (maximally 2 pages).
2. A detailed CV including a list of publications (if applicable).
3. Academic transcripts (for PhD candidates).
4. Contact information for at least two references.

Contact Information:
For further information about the position, please contact Professor Jing Tang at jing.tang at helsinki.fi<mailto:jing.tang at helsinki.fi>

About Us:
Network pharmacology for precision medicine group (https://www.helsinki.fi/en/researchgroups/network-pharmacology-for-precision-medicine) aims to develop computational tools to tackle biomedical questions that may potentially lead to breakthroughs in drug discovery. We are focusing on network pharmacology modelling, aiming at a systems-level understanding of how disease signalling pathways can be inhibited by synergistic drug combinations through multi-target perturbations. These methods offer an improved efficiency to identify more effective treatments for personalized medicine.

Join us in advancing personalized healthcare through innovative digital twin technologies and make a meaningful impact on cancer treatment!


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Jing Tang, PhD, Associate Professor, Academy of Finland Research Fellow
Network Pharmacology for Precision Medicine Group
Research Program in Systems Oncology, Faculty of Medicine
University of Helsinki, Finland
https://scholar.google.com/citations?user=6sNdZq8AAAAJ&hl=en
https://www.helsinki.fi/en/researchgroups/network-pharmacology-for-precision-medicine
https://twitter.com/netpharmed

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