Zur Startseite von DrArbeit.de,
der deutschlandweiten Stellenbörse für Diplomarbeiten und Doktorarbeiten


Lupe2

Archiv - Stellenangebot

 

Dies ist ein Angebot aus der Datenbank von DrArbeit.de

Um die Datenbank komfortabel nach weiteren Angeboten durchsuchen zu können, klicken Sie einfach oben oder hier.

 
Archiv-Übersicht     Angebot Nr. 13986

Angebotsdatum: 25. August 2020
Art der Stelle: Doktorarbeit
Fachgebiet: Chemie > Biochemie
Titel des Themas: Tumour targeting with polyligand approaches

Institut: LIMES Institute
Adresse:
Prof. Günter Mayer
Gerhard-Domagk-Str. 1
53123 Bonn
Tel.:    Fax.:
Bundesland: Nordrhein-Westfalen
Homepage: http://www.mayerlab.de
E-Mail Kontakt: mail

Beschreibung: The Mayer group (www.mayerlab.de) at the Life & Medical Sciences Institute of the University of
Bonn, Germany, has openings for two PhD students to complement the team in our endeavour to
realize personalized medicine approaches.

The first PhD project will be in the area of synthetic chemistry of oligonucleotides and dedicated to the generation of novel dendrimer structures to increase oligo-toxin and dye payload ratios. These dendrimer-oligos will then be applied in vitro and in vivo for tumour targeting and therapy approaches. Required skills: A solid background in chemistry or chemical biology and profound interest in biomedical topics.

The second PhD project will be in the area of targeting tumour tissue in vitro, ex vivo, and in vivo (mice). This individual will be involved in developing robotics-assisted procedure for generating enriched nucleic acid libraries that recognize tumour tissue ex vivo. Required skills: Background in chemistry, molecular biology, biochemistry or synthetic biology with a profound interest in tumour biology and treatment.

Both PhD projects are financed by an industrial sponsor for a duration of 3 years with an option for extension. The salary scale will be E13 TVL (65%).

Scientific background: Personalized medicine has attracted attention as superior diagnostic
approach to choose the potentially best helping drug among available treatments to defeat cancer.
In this approach, a multitude of data is gained to characterize molecular biomarkers of a patient’s
tumour. Based on this personalized tumour signature, a treatment with high probability being
effective is chosen. This approach is restricted by the availability of drugs, extensive molecular
profiling and the requirement of databases, recording and making available patient’s treatment
history and the benefit derived from an administered drug. A personalized therapy approach, in which a medication is rapidly and specifically developed for individual patients remains elusive though. The project PolyBiohybrid will apply design and selection strategies aiming at enriched nucleic acid libraries (eNAL) that can be used to target tumour tissue and which we have developed in preliminary studies (e.g., Domenyuk et al. Nature Communications 2017; Mayer et al., Nature Protocols 2010; Opazo et al., Molecular Therapy – Nucleic Acids, 2015). We will develop robotics assisted selection approaches to take this approach several important steps forward and generate eNALs, consisting of several thousands of different sequences recognizing a patient’s tumour. These eNALs provide a generic solution and represent long-sought compounds to generate personalized treatments for patients. The aim of this project is the generation of eNAL-based treatments built from at least two modular synthetic entities; one of which is cytotoxic and conjoined to eNALs specific for an individual patient’s tumour tissue. These biohybrid eNAL-chimeras will be used in vivo for the treatment of tumour disease. Polybiohybrid is highly interdisciplinary and will open novel routes for personalized drug development. It has implications ranging from life sciences to robotics, and from combinatorial (bio)chemistry to (pre)clinical sciences. As this approach is not restricted to one specific tumour type and will be applicable to other diseases, it bears an enormous innovative potential.
Please send inquiries and applications (including CV, description of background and a motivation
letter) directly to Prof. Günter Mayer by e-mail (gmayer@uni-bonn.de).
Methoden:
Anfangsdatum: 1. Dezember 2020
Geschätzte Dauer: 3 Jahre
Bezahlung:
Papers:
Sonstiges:

Archiv-Übersicht