The Wall Lab has an opening for a web developer. The position is available immediately and involves the design of mobile and web-based health applications that make diagnostic processes more efficient. Successful applicants must have superior programming skills and web design capabilities.

You will be designing a cloud-based web application for scientific research with multiple user login, administrative backend, and secure data collection and reporting.

Required Skills:

• Expertise in Python, HTML, MySQL, CSS, git (and github), and Unix command-line tools
• Experience in web development with Django or other Python web frameworks (Flask, Pyramid, etc.)
• Basic knowledge of system administration and security best-practices

Preferred:

• experience with Amazon Web Services or other cloud computing environments
• knowledge of encryption and secure transmission/storage of data and files
• Bachelor’s degree in Computer Science or related discipline
• Experience in team-based development
• Willingness to learn new applications

To apply for this position, please use our contact page to submit a cover letter and resume.

Great news segment on the approaches we’re working on. You can check it out here .

The process of diagnosing autism is complex, subjective, and often limited to only a segment of the population in need. With the recent rise in incidence to 1 in 88 children, the need for accurate and widely deployable methods for screening and diagnosis is substantial. Dennis Wall, associate professor of pathology and director of computational biology initiative at the Center for Biomedical Informatics at Harvard Medical School, has been working to address this problem and has discovered a highly accurate strategy that could significantly reduce the complexity and time of the diagnostic process.

Wall has been developing algorithms and associated deployment mechanisms to detect autism rapidly and with high accuracy. The algorithms are designed to work within a mobile architecture, combining a small set of questions and a short home video of the subject, to enable rapid online assessments. This procedure could reduce the time for autism diagnosis by nearly 95 percent, from hours to minutes, and could be easily integrated into routine child screening practices to enable a dramatic increase in reach to the population at risk.

“We believe this approach will make it possible for more children to be accurately diagnosed during the early critical period when behavioral therapies are most effective,” said Wall.

The first publication from this work has appeared online today, April 10, in Nature Translational Psychiatry. The article is available open access<a href=http://www.nature.com/tp/journal/v2/n4/full/tp201210a.html> here</a>.

Excerpt from the editorial : “We will accept in Translational Psychiatry only outstanding work, which a couple of years ago would have been published in Molecular Psychiatry and it is not currently in that journal solely for space reasons. An invitation from us to submit to Translational Psychiatry represents formal recognition that the work has the highest levels of intrinsic merit, impact and relevance” read more <a href=http://www.nature.com/tp/journal/v1/n4/full/tp20113a.html>here</a>.

International Autism Awareness Day takes place on April 2nd this year. People around the world will be illuminating buildings in blue and organizing other activities to generate awareness of autism and its impact on families and communities. Visit LightItUpBlue.org for suggestions on how you can be a part.

The Wall Lab focuses on understanding the complex genetics behind autism. Through our Autworks initiative, we provide tools for researchers and informational resources for families who have a family member with autism.