Postdoctoral Appointee - Applied Machine Learning
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Lemont, IL 60439
Postdoctoral Appointee \- Applied Machine Learning
Requisition Number: 403492 Location: Lemont, IL
Functional Area: Research and Development Division: LCF\-Leadership Computing Facility
Employment Category: Temporary 6 Months or Greater Education Required: Doctorate Degree
Level \(Grade\): 700 Shift: 8:30 \- 5:00 Share: Facebook LinkedIn Twitter
We invite you to apply for a postdoctoral appointee position with the ALCF\. In this role, you will join the Data Sciences group, a vibrant multi\-disciplinary team of scientists and High Performance Computing \(HPC\) software engineers, to work with large scientific datasets and carry out advanced analytical methods using data science and machine learning techniques\. You will collaborate with scientists in the ALCF Data Science Program \(ADSP\) who wish to gain insights into complex scientific problems using very large datasets produced by experimental, simulation, or observational methods\.
In the Data Sciences group, our postdoctoral researchers not only work at the forefront of HPC to push scientific boundaries, they routinely carry out research and development in state\-of\-the\-art machine learning and statistics techniques\. You will have a rare chance to work on some of the world’s largest supercomputers and upcoming data\-centric supercomputing systems to help solve significant real\-world problems\. At ALCF, you will be given the opportunity to interact with a wide variety of teams and application domains including engineering, material science, neuroscience, imaging, astrophysics and high energy physics\. ALCF researchers work in a highly collaborative environment involving science application teams, academia and industry, as well as other national labs and agencies, to solve some of the world’s largest and most complex problems in science and engineering\.
We expect you to have:
+ A PhD \(0\-3 years\) or equivalent experience in computer science, applied mathematics, statistics, computational sciences including physics, chemistry, engineering, and biology or in a related field\.
+ Considerable knowledge of one or more of machine learning, data mining and statistics\.
+ Significant experience in analysis of data with applications\.
+ Significant experience with analysis packages such as Matlab and R, and experience with one or more machine learning toolkits such as tensorflow, pytorch, caffe, scikit\-learn\.
+ Considerable knowledge and significant experience in one or more programming languages such as Python, C, C\, Java, and Scala\.
+ Good knowledge in mathematical optimization or linear algebra\.
+ Good communication skills both verbal and written\.
+ Considerable independent judgment and critical thinking\.
Desirable knowledge and skills:
+ Good experience and skills in interdisciplinary research involving mathematicians, computer scientists, and application scientists\.
+ Parallel computing experience is highly desirable\.
+ Collaborative skills including the ability to work well with other laboratories and universities, supercomputer centers, and industry\.
+ Ability to create, maintain, and support high\-quality software\.
+ Good publication record, preferably including first\-author publication\(s\)\.
As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation\. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment\. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law\.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Talent Recruitment Programs, as defined and detailed in United States Department of Energy Order 486\.1\. You will be asked to disclose any such participation in the application phase for review by Argonne’s Legal Department\.