PhD scholarship in bioinformatics of ayurvedic medicine sources and treatment response stratification

DTU Bioinformatics
Tuesday 31 Oct 17

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A PhD position - supported by Foundation Idella - is available at the Department of Bio and Health Informatics (DTU Bioinformatics) with a focus on ayurvedic medicine sources as well as treatment stratification using ayurveda concepts.

Responsibilities and tasks
Ayurvedic medicine, originated over 5000 years ago in India, is likely the earliest example of predictive, preventive, personalised and participatory (P4) medicine, which is drawing considerable contemporary attention in the area of health and disease. This ancient form of medicine is built on the individualised description of a patient, his/her environment and the disease. Ayurvedic treatment formulations also tend to be individualised with an understanding of body constitution and its interaction with diet and lifestyle. Most products used for treatment have natural sources of origin such as herbs and plants, and several controlled studies are now being designed to compare these against mainstream pharmacologically active agents in common disorders such as diabetes, schizophrenia, rheumatoid arthritis and other inflammatory conditions. The goals of this study are to, in collaboration with Indian scientists, a) determine compounds and mixtures that show efficacy in a controlled randomised trial for specific disease(s); b) advanced data integration of genomics, clinical factors and metagenomics, towards treatment prediction; and c) relating Ayurveda-principles based patient-stratification to treatment outcome in patients.

The project will focus largely on the bioinformatics aspects: data handling, integration and prediction. It is expected that knowledge of the ayurvedic system of individual classification and understanding ayurvedic substances, will be acquired during the PhD study. The work will build on our collaborations with Delhi University’s Department of Genetics, and co-supervision by Prof BK Thelma.

Qualifications
Candidates should have a master's degree in science or engineering or a similar degree with an academic level equivalent to the master's degree in engineering. The candidate must have some background in life sciences as well as strong computational skills. Experience with Linux/Unix, R and a scripting language is preferred. Prior experience with NGS, genome wide association analysis, ayurvedic medicine, microbiome analysis or machine learning would be considered an advantage.

Approval and Enrolment
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.

We offer
You will be working in the Disease Intelligence and Molecular Evolution group within an environment of energetic and dedicated colleagues. The group is one of several at the larger bioinformatics department with plenty of cross-collaboration. The head of department Prof Haja Kadarmideen will also be associated with the project.
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and an academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed with the relevant union. The period of employment is 3 years.

Further information
Further information may be obtained from Associate Professor Ramneek Gupta, email: ramneek@bioinformatics.dtu.dk

You can read more about the Department of Bio and Health Informatics on www.bioinformatics.dtu.dk

Please do not send applications to this e-mail address, instead apply online as described below.

Application
Please submit your online application no later than 21 November 2017. (Local time). Apply online at 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)

Candidates may apply prior to obtaining their master's degree, but cannot begin before having received it.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Bioinformatics has its main research and teaching activities in bio-medical and bio-technological informatics, metagenomics, epidemiology, quantitative genomics, integrative systems biology, artificial intelligence and machine learning. Research involves the use of vast amounts of phenotypic, clinical, environmental, biological and multi-omic information in humans, animals, plants and microbes. We run projects combining big data and laboratory research via the national supercomputing center or Computerome and the molecular genomics laboratories.

DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 5,800 advance science and technology to create innovative solutions that meet the demands of society; and our 11,000 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.

 

http://www.bioinformatics.dtu.dk/english/about/job/job?id=604a6d98-25c8-4f88-b164-37fe7d186981
21 NOVEMBER 2017