Location: Heidelberg, Germany
Staff Category: Staff Member
Contract Duration: 2 years
Grading: 4, 5 or 6; depending on qualification and experience
Closing Date: 3 January 2020
Reference Number: HD01657
A staff position as scientific programming and software engineering is available in the Statistical Genomics and Systems Genetics group at our laboratory in the Genome Biology Unit at EMBL Heidelberg in Germany.
Our research group is relocating from Cambridge to Heidelberg, where we bridge the excellence in molecular biology and biotechnology at EMBL Heidelberg with disease models and access to large biomedical datasets at the German Cancer Research Center Heidelberg.
Your role
The programmer will lead the development of Kipoi (http://kipoi.org), a software repository and API that seeks to unify recent advances in machine learning and deep neural networks for regulatory genomics. Kipoi builds on 3-way collaboration with international partners (Gagneur lab, LMU Munich, Kundaje lab, Stanford), and is increasingly used and extended by the research community. The position is funded via the recently awarded BMBF project MechML, which we are coordinating. The core aims of the post is to maintain and extend the Kipoi framework and its API, to implement new models within Kipoi and to support users of the system. We are also seeking to expand Kipoi to new fields and domains, including imaging and single-cell genomics. The latter aims are closely connected to the Human Cell Atlas, to which our group contributes as a node in the analysis working group.
You will be located in the Stegle group and collaborate with partners in the MechML projects, collaborators at EMBL, DKFZ and elsewhere. We seek to build on previous developments and expertise in the group, including in deep learning methods (see below). The position will be jointly located at EMBL Heidelberg and DKFZ.
You have
The successful applicant will hold a doctoral degree or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering with demonstrated experience in scientific programming, ideally combined with computational and statistical methods development.
Previous experience the management of substantial software projects is expected. Expertise in deep learning, the development of methods for genomics and genetics is beneficial, as is communicating results in scientific conferences and papers.
We especially seek candidates with prior experience in the development of software systems that utilize machine learning methods, including methods based on deep learning.
Proficiency with a high-level programming language (e.g., C++, Java) and/or appropriate scripting languages, and statistical data analysis tools such as R, MATLAB or Python is required.
The ideal applicant should have demonstrated the ability to work independently and creatively. (S)he should have excellent communications skills and be able to articulate clearly the scientific and technical needs, set clear goals and work within an interdisciplinary setting, communicating with other partners within the MechML project and within the Human Cell Atlas project.
Please apply online through our website by 3 Jan 2020.
