National Centre for Biological Sciences (NCBS), Bengaluru is inviting applications from suitable candidates for the post of Graduate Trainee in Integrative Structural Biology in the lab of Dr. Shruthi Viswanath for a temporary period purely on contractual basis.
Number of Position
Maximum of 1.5 yrs with a 3-month probation.
Education and Experience Required
- Education: BE/B.Tech or ME/MTech or MSc. Chemistry/Physics/Biology.
- Previous research experience in computational biology.
- Ability to understand and apply concepts from computational statistics, machine learning, and statistical physics.
- Programming experience in Python/C++ or any other language. To be demonstrated by its application to at least one completed research/development project.
- Comfortable working in a Linux environment.
Ideal Candidate Profile
The ideal candidate possesses strong quantitative skills and is motivated to apply these skills in the structural biology/cell biology domains.
The candidate will ideally possess experience in computational biology research and interested in a research career in the long term.
The candidate will be working on one of the following projects.
Project (1): Integrative structure modelling of large protein assemblies.
Structures of protein complexes contribute to our understanding of mechanistic details of biological processes and the roles of proteins in disease. However, structures of large protein assemblies are difficult to obtain using any single experimental method.
Integrative modeling is an approach to determine such structures by using a variety of experimental data, physical theories, and statistics of existing structures. The project involves developing methods to make modeling more accurate and efficient, specifically developing methods to improve model representation and validate the models.
Project (2): Annotating cellular tomograms
Recent improvements in imaging have led to a vast increase in high-resolution 3D images of cells (cryo-electron tomography). Since this technique allows us to image complete cells in an unperturbed way, it is tremendously useful for understanding the nano-scale organization of cells.
We will be developing machine learning methods for automatically annotating large complexes and organelles in tomograms. These will enable interesting quantitative comparisons between cells at different stages, as well as between normal and diseased cells.
25,000 (without CSIR/GATE/equivalent qualification), 31000 + 24% HRA (with CSIR/GATE/equivalent qualification)
How to Apply?
Interested applicants are requested to apply with their CV and a short project proposal based on one of the two topics above (~300 words) to firstname.lastname@example.org. Project proposals not related to the above topics and incomplete applications missing one of the two documents will not receive any response.
The last date for applying is 31st March, 2020. Candidates will be contacted and interviewed on a rolling basis until the position is filled. Please note that candidates who have not been selected for an interview will not be contacted.
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