The CUNY ASRC Structural Biology Initiative seeks applications from individuals with experience in software development and computational biology, computer science, biology or chemistry to serve as computational scientists. Several positions are available and the job description and level is dependent on the skills, experience and career goals of the candidates.
The position involves developing advanced desktop software for the analysis of structural biology data in the Java programming language. Developing of these tools would involve, depending on the candidates skills, programming graphical user interfaces, developing tools using statistical and machine learning algorithms, implementing deep learning based algorithms, signal processing, and/or programming GPUs for rapid calculations.
Other Duties
Other duties may include:
- Maintaining hardware and software
- Writing documentation
- Developing software test suites
- Training users in use of the developed software
Qualifications
Successful candidates must have significant experience in software development with the Java programming language and should have an interest in computational science. Experience with new machine learning technologies such as deep neural networks, and GPU programming would be an advantage. Other desirable skills (depending on the exact position) include applied mathematics, and software engineering skills (including source code management, integrated testing and documentation).
Minimum Qualifications (depending on position)
- A Master’s Degree (or Bachelors with significant computational experience) from an accredited institution in Chemistry/Biochemistry/Computational Biology/Computer Science.
- Software development experience in Java
- Experience using standard software engineering tools including source code control (such as Git), integrated development environments (such as NetBeans), project management tools (such as Maven) and test suites (such as Junit).
Preferred Qualifications
- Coursework and/or experience in biochemistry.
- Course work or experience in numerical methods.
- Course work or experience in data mining and statistics
