We are seeking a Postdoctoral Research Assistant for the Gene Machines’ group, led by Professor Achilles Kapanidis. The group is well known for developing single-molecule fluorescence methods (Holden Nature Meth 2011, 8, 279; Crawford Biophys J 2013, 105, 2439) and applying them to DNA/RNA polymerases (Hohlbein Nature Comm, 2013, 4, 2131; Stracy M PNAS 2015; 112, E4390).
The project is funded by the Wellcome Trust and focuses on single-molecule fluorescence analysis of gene transcription. You will develop software tools and algorithms to collect and analyse large data sets generated from single-molecule imaging and super-resolution microscopy studies of RNA polymerase and transcription proteins either on glass surfaces or inside living bacteria. You will manage academic and administrative activities, develop ideas for generating research income, collaborate on reports and journal articles, and have the opportunity to teach.
The ideal candidate should possess (or be close to obtaining) a doctorate in computer science or a related field, and have knowledge of C/C++, Java, CUDA and MATLAB. Experience in image analysis, time-series analysis, machine learning, and statistics is essential. Experience with parallelised data analysis software, automation algorithms, and data storage solutions is desirable. Experience in single-molecule fluorescence, particle tracking, localisation microscopy and quantitative cell imaging is also desirable. You should also have a strong publication record, excellent communication skills and able to work effectively within an interdisciplinary group.
Please direct enquiries to Professor Kapanidis ([email protected]).
You will be required to upload a statement of research interests, CV, copies of two representative publications and details of three referees as part of your online application.
Only applications received before 12.00 midday on Monday 19 September 2016 can be considered.