|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||Not Specified|
|Placed On:||31st March 2020|
|Closes:||31st August 2020|
South Kensington Campus
To start as soon as possible, by negotiation. Closing date 31st Aug 2020
The Department of Computing is a leading department of Computer Science among UK Universities, and has consistently been awarded the highest research rating from the Higher Education Funding Council. In the 2014 REF assessment, the Department was ranked third (1st in the Research Intensity table published by The Times Higher), and was rated as "Excellent" in the previous national assessment of teaching quality.
Imperial’s Department of Computing are seeking a motivated PhD student to work on a project to develop machine learning models and tools to decode signals from DNA sequences faster. The algorithm(s) will be developed and improved before implementation in an open-source and user-friendly software package.
The project is carried out in the context of the EC project OligoArchive (https://oligoarchive.eu) which has the goal of developing a prototype for the storage of information in synthetic DNA. The PhD project will develop the means to decode the synthetic DNA faster through the use of machine learning models and through assumptions about the information stored in the DNA (as opposed to natural DNA where no such assumptions can be made). The post holder will:
The post holder will work at Imperial’s SCALE Lab (http://scale.doc.ic.ac.uk/). The project allows for some flexibility in the profile of applicants. Candidates with expertise in the following areas can be a good fit:
All applicants should be able to demonstrate the following:
The successful applicant will have an MSc (or equivalent) in an area pertinent to the subject area, ideally computer science.
How to apply:
Please forward your CV to Dr. Thomas Heinis: firstname.lastname@example.org
Applicants are advised to visit http://www.imperial.ac.uk/computing/prospective-students/courses/phd/ for general information on becoming a PhD student.
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