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This project aims to to develop an innovative, modular, and partially bioresorbable wound filler for Negative Pressure Wound Therapy (NPWT) based on natural biopolymers, addressing the clinical limitations of conventional polyurethane dressings. The proposed system aims to enhance tissue regeneration, prevent excessive granulation, and facilitate wound access and monitoring. We will integrate cutting-edge computational design and advanced manufacturing techniques, including high-throughput hydrogel screening, machine learning-assisted material optimization, and microfluidic platforms for precise control of porous architecture. This synergistic approach will enable the creation of tailored, multifunctional wound dressings that align with clinical requirements and sustainability goals.

PhD student 1:

• creation of a hydrogel library and performing mechanical characterization of materials
• production of dressings and validation tasks
• presentation of results and their dissemination

PhD student 2:

• performing  numerical simulations
• developong new genetic algorithms related to finite element (FE) modeling
• presentation of results and their dissemination     

-PhD student/stipend holder position in the Institute of Physical Chemistry PAS within the project FENG.02.02-IP.05-0180/24 “Inverse design-assisted biodegradable modular dressings for negative pressure wound healing”.

The project is financed under Action 2.2 “Intellectual Property for the Development of Companies”, Priority II “Environment Conducive to Innovation”, of the European Funds for Smart Economy 2021–2027 (FENG). The Intermediate Body is the Foundation for Polish Science (FNP)

- the opportunity to work in an interdisciplinary, international research team

- engagement into an ambitious research program and possibility to build the academic career

Institute provides an opportunity to participate in ERASMUS+ programme.

The selected candidates will be part of a highly experienced, multidisciplinary team. They will have the opportunity to expand their knowledge and confront new tasks resulting in new technical solutions and applications.

PhD Student 1 :

• Master degree in chemistry, material science,  biomedical engineering or related fields
• prior experience in bio materials and porous materials
• fluency in spoken and written English
• excellent communication, organization and time management skills

PhD Student 2:

• Master degree in computer science, AI, machine learning or related fields
• Prior experience in CFD, ANSYS, COMSOL
• fluency in spoken and written English
• excellent communication, organization and time management skills

The committee will consider the following criteria:

• Competence to carry out specific tasks in the research project
• Previous scientific achievements
• Fluency in English