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Job Description

Data Scientist for machine learning, computer vision, and neuroscience projects


The Kumar Lab at the Jackson Laboratory consists of geneticists, neuroscientists, and computer scientists who are passionate about discoveries of novel targets and models for mental illness through innovation at the confluence of computational, genetic, and genomic methods. We combine traditional behavioral and neuroscience methods with modern computer vision and machine learning methods to understand how genes shape the nervous system and how this, in turn, leads to altered behaviors. We believe that by taking this multimodal approach to problem solving we will make impactful discoveries for diagnosis and treatment of mental illness. We are recruiting a data scientist for this project to join an existing team of two engineers for a project that is fully funded for three years. A typical project may involve determining behavioral changes that occur in short vs long term time scale in mice due to exposure to addictive or mood-altering substances. Linking these behaviors to specific genetic variants. Scoring sleep states visually without the need for electrode-based EEG/EMG recordings and linking sleep disturbances to addiction behaviors. Since the team has two computer vision scientists, behaviorists, and neuroscientist, no experience is required within these fields. Instead, intellectual curiosity and the ability to work across fields at the interface multiple fields are required. The successful candidate will receive credit for their work through authorship on academic papers and patents.

Key Responsibilities:

• Use outputs from computer vision and machine learning techniques to quantify and analyze mouse behavioral data (video-based).

• Expand those tools to new environments, behaviors, and multiple mice.

• Design and manage relevant training datasets to achieve these tasks.

• Carry out multidimensional and multivariate statistical analysis and modeling of these data.

• Lead and contribute to scientific journal articles.

• Statistical modeling


• Minimum of five (5) years of experience and a BS or a higher degree in computer science or informatics, or significant prior work experience in data analysis for scientific research

• The successful candidate will have working familiarity with a majority of the following technologies: R statistical environment, big data analysis, HPC (SLURM, Torque, singularity), Tensorflow or PyTorch Recommended: these skills are available in the group and will be taught

• Machine Learning and computer vision – opportunities to learn state of art machine vision will be offered

• GPU Compute Familiarity

• Big Data Management

• Behavioral psychology and genetics

• Experience with Tensorflow, PyTorch or Keras

• Be willing represent the Lab at CS meetings and conferences.

• Ability to explain data to non-computer scientists is encouraged.


JAX began in 1929 with a small group of scientists dedicated to the emerging field of genetics. We now have over 1,700 scientists, technicians, and support staff, including over 50 Principle Investigators in five primary disease areas: cancer, reproductive biology, immunology, metabolic processes and neuroscience. Our fundamental contributions to biomedical research have established the mouse as the premier research animal model.

• Uncover more of our historic milestones, including the 26 Nobel prizes associated with our research, resources, and education. Follow the progress we’re making on our quest to improve human health via our recent research highlights.

• The Kumar Laboratory has core expertise in addiction genetics and is comprised of seven engineers, neurophysiologists, and statistical geneticists.

• JAX information technology group hosts two high performance compute clusters, and 48 state of the art NVIDIA Tesla V100/P100 GPUs with systems administrators and HPC experts are on staff.

• A highly collaborative computational sciences group at JAX has 30+ PhD level software engineers, biostatistician, and software engineers

• The JAX Courses and Conferences is available to all employees and offers intensive lectures and hands of training from leading world experts on human health and disease.

• The Bar Harbor campus is nestled in the Acadia National Park, ideal for outdoor activities.

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  • Location Maine
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