Postdoc in Computational Biology: Algorithms and FPGA Hardware for 3rd Generation DNA Sequencing
Application deadline: July 2, 2017
Lab Description: The Electronic Machine Intelligence Lab (EMIL) in York University’s Electrical Engineering and Computer Science (EECS) Department develops custom hardware for applications in computational biology. The lab’s research covers custom and semi-custom analog/digital very-large-scale integrated (VLSI) systems as well as field-programmable gate-arrays (FPGAs) and other hardware acceleration means (e.g. graphics processing units – GPUs).
Position Summary: EMIL has an exciting interdisciplinary position available for a post-doctoral research fellow (PDF) working in the emerging area of computational hardware design for base calling on strand-sequenced DNA data in a mobile/embedded context (e.g. field genomics, metagenomics). Under the direction of the principal investigator the successful candidate will be involved in a collaborative effort focused on the design of real-time deep learning labelling algorithms for DNA sequencing data and the translation of these algorithms into FPGA hardware intended to achieve higher computational speed and efficiency. The position requires designing and testing high-speed DNA base calling software and associated hardware in collaboration with the Canadian Food Inspection Agency (CFIA) and IBM Corp.
The deadline for application packages is July 2, 2017. Interested individuals should send their CV with a list of references via email to: firstname.lastname@example.org.
Your email / cover letter should be addressed to:
Department of Electrical Engineering & Computer Science
Lassonde School of Engineering
Lassonde Bldg. 1012B
4700 Keele St
Toronto, ON, Canada M3J 1P3
|Important Notes:||• This is a full-time 2-year postdoctoral appointment.
• This position is represented by a union (the York University Faculty Association) for collective bargaining purposes.
• Work will be performed predominantly at York University’s Keele campus (4600 Keele St., Toronto, ON), but will require occasional visits to the CFIA’s Ottawa and Manitoba food safety facilities for training plus system implementation and test.
|Specific Responsibilities:||• Analyze 3rd generation sequencing data.
• Collaborate with other systems designers in developing machine learning algorithms and software for the base calling of strand-sequenced data.
• Work with hardware designers in translating base calling algorithms to FPGA hardware.
• Work with the CFIA in the integration of developed software and hardware into their sequencing pipeline.
• Prepare research results for presentation at internal and international scientific/engineering meetings as well as academic journals.
|Requirements:||• PhD within the last 5 years in electrical engineering, computer science, bioinformatics, biology, genetics, or related fields
• Experience with FPGA (Altera/Xilinx) development
• Experience in FPGA design and coding
• Competency in computer languages (e.g. C, C++, Python) and software stack development
• Competency with scripting languages (e.g. Perl)
• Excellent written and oral communication skills
|Additional Desired Qualifications:||• Experience with machine learning techniques for sequence labelling
• Experience with primary and secondary sequence analysis techniques (e.g. on next-generation sequencing data)