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Postdoctoral Research Associate

tolgatasdizen – Posted on September 11, 2017 at 5:08 pm –

The Scientific Computing Imaging Institute (SCI) at the University of Utah conducts original research to establish the scientific capabilities that govern the design, performance, and integration of computational tools into scientific platforms. In this position, you will be an employee of the University of Utah and have an appointment at Idaho National Laboratory. As a member of the team that spans the University of Utah, Idaho National Laboratory, and Oak Ridge National Laboratory you will provide analytical and programming expertise in the use-inspired and application of deep learning to support basic and applied research for Idaho National Laboratory.

As an experienced postgraduate researcher for the applied optimization or machine learning you will ensure that state-of-the-art methods are applied within a growing national laboratory and university team to unlock the full potential of advanced microscopy and materials characterization. You will run and lead projects in a wide variety of applications to bring about scientific and technology benefits to our team by challenging and collaborating with other scientists, professors, engineers, and business professionals on the utility and application of novel image reconstruction and analysis approaches, and spectral analysis approaches to provide ground-breaking capabilities for material science applications. You will work in interdisciplinary team comprised of scientists, engineers, and business professionals to realize the full potential and utility of deep learning for unlocking the potential revolutionary speed-ups to data access and extraction of microscopy datasets.

For example, you will improve on the utility and design of data science tools for microscopy that realize new paradigms in data acquisition, information storage, and technique development using these advanced tools and software packages. You will optimize the data science tools and developments across several installations including national laboratories and universities. Based on the development you will deploy trained models that forecast and suggest alternatives to sampling materials data for realizing the temporal, spatial, and spectral limits. Based on your developed and trained models you will discuss and present these improvements with members of top universities and national laboratories at professional conferences, meetings, and high impact peer reviewed publications. 
With your expertise, you will also help to identify new application areas, use cases, or technologies by applying your innovative data analytics methods and technologies. As the team is a collaboration between Idaho National Laboratory and the University of Utah, you will have the chance to actively involve yourself in the field of advanced microscopy and data science at both institutions.

• Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
• Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive understanding of microscopy data structures and metrics. Advocate for changes in data storage and access file systems where needed.
• Develop and implement novel image reconstruction and analysis approaches for microscopy using deep learning and machine learning packages.
• Develop and implement novel spectral analysis and approaches.
• Develop novel approaches for high-content imaging
• Interact and work in an interdisciplinary cross-functioning team to develop and validate software tools for material research and microscopy applications. Work closely with scientists and engineers to identify opportunities for, design, and assess improvements to envisioned final products.

Minimum Qualifications:
• PhD degree in Physics, Computer Science, Electrical Engineering or related technical fields, or equivalent practical experience
• 2 years of relevant work experience in data analysis or related field. (e.g., as a statistician / data scientist / material scientist/ physicist).
• Experience with programming software (e.g. R, Python, C/C++, Linux, MATLAB, Labview) and database languages (e.g., SQL). 
• Experience implementing image processing and reconstruction algorithms.
• Experience with machine learning (Tensorflow, Caffe2, PyTorch, MxNet)
• Proven experience in applying creative and practical Data Science methodologies to extract, process and transform data from multiple sources

Preferred Qualifications
• 4 years of relevant work experience in data analysis or related field. (e.g., as a statistician / data scientist / material scientist/ physicist), including deep expertise and experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods. Analytical engagements outside class work while at school can be included.
• Applied experience with machine learning on large datasets.
• Experience in mathematics and algorithms.
• Experience with material science and/or metallurgy.
• Good communication and collaboration skills.

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