Partner search: Cluster IMMUNTEL – Immune Technologies
The Fraunhofer Institute for Cell Therapy and Immunology currently submitted a application for a recent funding initiative published by the German Federal Ministry of Education and Research. The call is focusing on internationalization of German industry/academia clusters.
Our current cluster organization IMMUNTEL addresses 6 main technology areas within the „immune technologies“ field: – New therapeutic approaches for cancer based on different forms of immunmodulation (esp. DC-Vaccine, CAR-T-cells i. a.) – Immunmodulatory methods for treatment of inflammatory and autoimmune diseases – Innovative vaccines for human and veterinary medicine treatments (esp. DNA-vaccine, composite-vaccine) – New technologies for manufacturing and quality control systems for therapeutics including the required medical technology – Methods of medical technology for function analysis of immune system (innovative diagnostics) – New detection systems for immunotoxic and allergenic substances within the field of environmental immunology
Main aim of the BMBF call is to support cluster initiatives regarding their internationalization attempts. Thus, cluster members shall get supported in their efforts to conquer international markets and to benefit from joint R&D projects with international partners (the selected international partner should take care on providing counterfinancing at a similar level for activities/project parts in the respective region/country). Target regions we currently work with:
– South Korea (Jeollanam-do province) – Canada (Ontario/GTA/Hamilton) – ScanBalt ® fmba – South Africa (Stellenbosch University Cluster)
Now we are looking for a cluster within the ScanBalt Metacluster in our field of research, with strong industrial members and interest in a collaboration with Germany.
Cluster Manager of IMMUNTEL
Dr. Thomas Tradler Thomas.firstname.lastname@example.org
Mobile: +49 (0)176 101 44 255
13 October 2017
A really competitive advantage up here
12 October 2017
PhD in computational disease systems biology