Machine Learning Researcher - Funke Lab

Summary:

The Funke lab is looking for a Machine Learning Researcher who is excited about the development and application of computer vision and machine learning methods in the context of the life sciences. More specifically, we are interested in topics that facilitate the analysis of large electron and light microscopy datasets. We would love to hear from you, if you are excited about any of the following topics:

• Segmentation and Classification of Biological Structures

• Tracking and Event Detection in 2D and 3D Movies

• Unsupervised, Weakly-Supervised, and Interactive Learning

• Explainable AI for Unbiased Machine-Discovery

• Processing of Very Large Datasets

• Scientific Software Development for Experimentalists

Recently, Janelia set course for its second research area "4D Cellular Physiology". Our lab has a solid background in the analysis of large neuroscience datasets and we are now looking forward to opening up our work to the broader field of physiology. Future datasets will be diverse and pose new challenges for computational methods: We will collect large, high-resolution electron microscopy datasets of cells in their native tissue environment, together with functional, spatio-temporal light microscopy recordings.

Computational methods will be needed to annotate and analyze those datasets, as well as to relate function and structure, to ultimately help turning images into scientific discoveries. We invite you to join us in developing methods that have real-world applications, are necessary to further our understanding of biology, and that have an immediate impact on Janelia's research.

At Janelia, you will have the unique opportunity to join a highly collaborative environment and work together with leading experts in the fields of cell biology, neuroscience, microscopy, biochemistry, machine learning, and computer vision. Several support teams at Janelia (including software engineers in Scientific Computing) are available to help develop your ideas beyond academic proofs of concepts, and turn them into usable tools in the hands of experimentalists.

Qualifications:

Education:

• PhD in Computer Science, Machine Learning, Applied Math, Physics, or related field

• Advanced knowledge of Machine Learning, Statistics, Calculus, Data Structures, and Algorithms

Skills and Abilities:

• Strong background in computer vision, machine learning, or scientific software development

• Experience with large microscopy datasets, deep-learning frameworks, Python, C/C++, or software design are a plus

• Enthusiasm for using computational approaches to learn to discover biological insights

For more information please visit our lab page https://www.janelia.org/lab/funke-lab or send your CV/questions directly to Jan at (). We are looking forward to hearing from you!

Physical Requirements:

Remaining in a normal seated or standing position for extended periods of time; reaching and grasping by extending hand(s) or arm(s); dexterity to manipulate objects with fingers, for example using a keyboard; communication skills using the spoken word; ability to see and hear within normal parameters; ability to move about workspace. The position requires mobility, including the ability to move materials weighing up to several pounds (such as a laptop computer or tablet).

Persons with disabilities may be able to perform the essential duties of this position with reasonable accommodation. Requests for reasonable accommodation will be evaluated on an individual basis.

Please Note:

This job description sets forth the job's principal duties, responsibilities, and requirements; it should not be construed as an exhaustive statement, however. Unless they begin with the word "may," the Essential Duties and Responsibilities described above are "essential functions" of the job, as defined by the Americans with Disabilities Act.

Compensation and Benefits

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Compensation Range

Pay Type:

HHMI's salary structure is developed based on relevant job market data. HHMI considers a candidate's education, previous experiences, knowledge, skills and abilities, as well as internal equity when making job offers. Typically, a new hire for this position in this location is compensated between the minimum and the midpoint of the salary range.