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<p class="MsoNormal"><b><span lang="EN-GB">PhD Student or Post-Doc Position in Digital Twins Modelling of Drug Responses for Cancer Patients<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Position Title:</span></b><span lang="EN-GB"> PhD Student or Post-Doctoral Researcher in Digital Twin Modelling<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Location:</span></b><span lang="EN-GB"> Faculty of Medicine, University of Helsinki, Finland<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Duration:</span></b><span lang="EN-GB"> 3 years (full-time)<o:p></o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Application Deadline: March 1, 2025<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">About the Project:<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB">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
<b>DTRIP4H</b> (<a href="https://www.dtrip4h.eu/">https://www.dtrip4h.eu/</a>). 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.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Position Overview:<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB">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.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Key Responsibilities:<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB">- Develop and refine computational models for digital twins of cancer patients.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">- Integrate multi-omics data (genomics, transcriptomics, proteomics) and clinical data into the models.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">- Apply machine learning and AI techniques to predict drug responses and optimize treatment strategies.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">- Collaborate with a multidisciplinary team of cancer researchers, clinicians, and data scientists.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">- Publish research findings in high-impact scientific journals and present at international conferences.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Qualifications:<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB">- For PhD Candidates:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> - A Master’s degree in Bioinformatics, Computational Biology, Biomedical Engineering, Computer Science, or a related field.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> - Strong background in computational modelling, machine learning, or data analysis.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> - Proficiency in programming languages such as Python, R, or MATLAB.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> - Excellent written and verbal communication skills in English.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> - Prior experience in cancer research or personalized medicine is a plus.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">- For Post-Doc Candidates:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> - A PhD in Bioinformatics, Computational Biology, Biomedical Engineering, Computer Science, or a related field.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> - Proven track record of research in computational modeling, machine learning, or biomedical data analysis.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> - Strong publication record in peer-reviewed journals.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> - Experience with multi-omics data integration and analysis.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"> - Excellent project management and teamwork skills.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">What We Offer:<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB">- A stimulating and collaborative research environment.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">- Access to state-of-the-art computational resources and datasets.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">- Opportunities for professional development and networking within the EU DTRIP4H consortium.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">- Competitive salary and benefits package according to institutional standards.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">How to Apply:<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB">Interested candidates should submit the following documents to
<a href="mailto:jing.tang@helsinki.fi">jing.tang@helsinki.fi</a> by March 1, 2025:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">1. A cover letter outlining your research interests and motivation for applying (maximally 2 pages).<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">2. A detailed CV including a list of publications (if applicable).<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">3. Academic transcripts (for PhD candidates).<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB">4. Contact information for at least two references.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">Contact Information:<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB">For further information about the position, please contact Professor Jing Tang at
<a href="mailto:jing.tang@helsinki.fi">jing.tang@helsinki.fi</a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB">About Us:<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB">Network pharmacology for precision medicine group (<a href="https://www.helsinki.fi/en/researchgroups/network-pharmacology-for-precision-medicine">https://www.helsinki.fi/en/researchgroups/network-pharmacology-for-precision-medicine</a>)
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<b>
</b>understanding of how disease signalling pathways can be inhibited by synergistic drug<b>
</b>combinations through multi–target perturbations. These methods offer an improved<b>
</b>efficiency to identify more effective treatments for personalized medicine.<o:p></o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-GB">Join us in advancing personalized healthcare through innovative digital twin technologies and make a meaningful impact on cancer treatment!<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="font-size:8.0pt;color:#1F497D;mso-ligatures:none">-------------------------------------------------------------------------------------------------------------<o:p></o:p></span></b></p>
<p class="MsoNormal"><b><span style="font-size:12.0pt;color:#1F497D;mso-ligatures:none">Jing Tang</span></b><span style="font-size:12.0pt;color:#1F497D;mso-ligatures:none">, PhD, Associate Professor, Academy of Finland Research Fellow<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;color:#1F497D;mso-ligatures:none">Network Pharmacology for Precision Medicine Group<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;color:#1F497D;mso-ligatures:none">Research Program in Systems Oncology, Faculty of Medicine<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;color:#1F497D;mso-ligatures:none">University of Helsinki, Finland<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;color:#1F497D;mso-ligatures:none"><a href="https://scholar.google.com/citations?user=6sNdZq8AAAAJ&hl=en"><span style="color:#0563C1">https://scholar.google.com/citations?user=6sNdZq8AAAAJ&hl=en</span></a><o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;color:#1F497D;mso-ligatures:none"><a href="https://www.helsinki.fi/en/researchgroups/network-pharmacology-for-precision-medicine"><span style="color:#0563C1">https://www.helsinki.fi/en/researchgroups/network-pharmacology-for-precision-medicine</span></a><o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:12.0pt;color:#1F497D;mso-ligatures:none"><a href="https://twitter.com/netpharmed"><span style="color:#0563C1">https://twitter.com/netpharmed</span></a><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-GB"><o:p> </o:p></span></p>
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