6 March, 2016
Identification of T cell epitopes constitutes a critical part of novel approaches for rational vaccine design and development of diagnostics. Sequence based T-cell epitope predictions have improved immensely in the last decade. Methods have been developed that produce highly accurate binding predictions for prevalent alleles in humans, non-human primates, and life-stock animals like swine and cattle. CBS (center for biological sequence analysis) is leading the field of immunoinformatics and the methods developed at CBS for prediction of peptide MHC binding have in many independent benchmark calculations been demonstrated to be second to none.
A central part of the PhD will be dedicated to implement and develop improved methods for prediction of peptides binding to MHC class I and II molecules maintaining the edge of the CBS methods for MHC peptide binding prediction. The development of improved methods will include novel consensus approaches integrating artificial neural network, stabilization matrix, pickpocket, and similarity-kernel-based predictions, as well as the setup of automated schemes for retraining and/or evaluation of prediction methods as new peptide binding data become available from our collaborators.
Another part of the PhD will be dedicated to investigate the role of T cells in epitope discovery, and the development of methods for prediction of immuno-dominance and T cell cross reactivity. This will involve development of a predictor for how the TCR (T cell receptor) interacts with the MHC-peptide complex.
Lastly, the PhD will in collaborations with research partners working on vaccine development in general and cancer immunotherapy in particular, use the tools developed within the group to construct improved methods for identification of immunogens.
The successful candidate will have a bioinformatics, biology, or computer science background and must have strong computational skills and prior experience with Unix/Linux command line environments, as well as either C, Perl, Python or a comparable scripting language. The applicant must have prior experience with bioinformatics and high-performance machine learning methods. Knowledge of systems biology, immunology, and structural biology is considered a plus.
Candidates should have a master’s degree in engineering or a similar degree with an academic level equivalent to the master’s degree in engineering.
The scholarships for the PhD degree are subject to academic approval, and the candidates will be enrolled in one of the general degree programmes of DTU. For information about the general requirements for enrolment and the general planning of the scholarship studies, please see the DTU PhD Guide ([link]).
We offer an interesting and challenging job in an international environment focusing on education, research, public-sector consultancy and innovation, which contribute to enhancing the economy and improving social welfare. We strive for academic excellence, collegial respect and freedom tempered by responsibility. The Technical University of Denmark (DTU) is a leading technical university in northern Europe and benchmarks with the best universities in the world.
Salary and appointment terms:
The salary and appointment terms are consistent with the current rules for PhD degree students. The period of employment is 3 years.
HOW TO APPLY:
Further information may be obtained from Morten Nielsen, mniel[at]cbs.dtu.dk
Please do not send applications to this e-mail address, instead apply online as described below.
Apply at http://www.career.dtu.dk
Applications must be submitted as one pdf file containing all materials to be given consideration. To apply, please open the link “Apply online,” fill in the online application form, and attach all your materials in English in one pdf file. The file must include:
* A letter motivating the application (cover letter)
* Curriculum vitae
* Grade transcripts and BSc/MSc diploma (an official translation into English)
* Excel sheet with translation of grades to the Danish grading system (see guidelines and excel spreadsheet here: [link])
Candidates may apply prior to obtaining their master’s degree, but cannot begin before having received it.
The assessment of the applicants will be made by Morten Nielsen.
Please submit your online application no later than 15 April 2016.
All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.
DTU Systems Biology’s academic profile covers the fields of cellular, molecular and structural biology, bioinformatics, computational biology, industrial biotechnology, biomedicine and health. Systems biology addresses both the overall properties of a biological system and uses scientific approaches to understand specific mechanisms. Therefore, much of the work carried out by our research groups is characterized by the incorporation of several academic disciplines.
Fundamental biological research constitutes the point of departure for technological activities at DTU Systems Biology, and we put great emphasis on transforming scientific perceptions into advanced technical applications. This applies to our research as well as to our study programmes. DTU Systems Biology has approx. 260 employees, comprising faculty members, PhD, technicians and administrative staff.
DTU is a technical university providing internationally leading research, education, innovation and public service. Our staff of 5,800 advance science and technology to create innovative solutions that meet the demands of society; and our 10,300 students are being educated to address the technological challenges of the future. DTU is an independent academic university collaborating globally with business, industry, government, and public agencies.
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