Los Alamos National Laboratory Computer Vision and Machine Learning Postdoc in Los Alamos, New Mexico
What You Will Do
The Information Sciences group (CCS-3) at the Los Alamos National Laboratory (LANL) has an opening for an outstanding postdoctoral research associate in the areas of computer vision and machine learning for technical images. Computer vision, especially when combined with machine learning methods, has dramatically improved the ability to detect objects in images and semantically segment images for scene understanding. However, these advances have not yet automated the understanding of information contained in hand-drawn figures, technical diagrams, mathematical equations, data plots, and other images conveying technical information, because those types of images contain much less information compared with natural images.
A successful candidate will engage in two or more of the following focus areas:
1) Develop computer vision algorithms for shape matching across a wide variety of image types including photographs, drawings, diagrams, scanned historic documents, etc.
2) Develop methods for representation learning, metric learning, or graph-based machine learning that capture semantically-meaningful spatial information and relationships among objects in images.
3) Develop computer vision and machine learning algorithms for image analysis (classification, object detection, segmentation, image retrieval) that require very little or no labeled training data (zero-shot, one-shot, and transfer learning; or domain adaptation/generalization); and allow end-users to quickly customize machine learning models to novel problems (model selection, interactive learning, and workflow automation).
What You Need
Minimum Job Requirements:
Research-level expertise in one or more of the above focus areas
Demonstrated ability to publish research in top peer-reviewed journals or conference proceedings
Strong programming skills
Research-level expertise in two or more of the above focus areas
Research experience in using graphs for image analysis
Demonstrated ability to work in interdisciplinary project teams and learn about other fields
Education: Ph.D. in computer science, computer vision, machine learning, imaging science, mathematics, electrical engineering, statistics, data science, or a closely related discipline completed within the past five years or to be completed soon prior to employment.
Note to Applicants:
In addition to submitting a CV, applicants must include a cover letter describing their research interests.
Postdoctoral appointments are for two years, with the possibility of a third year extension.
Where You Will Work
Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. Our generous benefits package includes:
§ PPO or High Deductible medical insurance with the same large nationwide network
§ Dental and vision insurance
§ Free basic life and disability insurance
§ Paid maternity and parental leave
§ Award-winning 401(k) (6% matching plus 3.5% annually)
§ Learning opportunities and tuition assistance
§ Flexible schedules and time off (paid sick, vacation, and holidays)
§ Onsite gyms and wellness programs
§ Extensive relocation packages (outside a 50 mile radius)
Directive 206.2 - Employment with Triad requires a favorable decision by NNSA indicating employee is suitable under NNSA Supplemental Directive 206.2 . Please note that this requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A.
Position does not require a security clearance. Selected candidates will be subject to drug testing and other pre-employment background checks.
New-Employment Drug Test: The Laboratory requires successful applicants to complete a new-employment drug test and maintains a substance abuse policy that includes random drug testing.
Equal Opportunity: Los Alamos National Laboratory is an equal opportunity employer and supports a diverse and inclusive workforce. All employment practices are based on qualification and merit, without regard to race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation or preference, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal laws and regulations. The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request such an accommodation, please send an email to email@example.com or call 1-505-665-4444 option 1.
Vacancy Name: IRC84091
Organization Name CCS-3/Information Sciences
Req ID: IRC84091