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UID:submissions.supercomputing.org_SC20_sess280_job121@linklings.com
SUMMARY:TACC - Research Engineering Scientist Associate
DESCRIPTION:Job Posting\n\nTACC - Research Engineering Scientist Associate
 \n\n\n\nThe Research Engineering and Science Associate (RESA) is a positio
 n in the Scalable Computational Intelligence (SCI) group at TACC. The indi
 vidual will contribute to research, development, and support activities in
 volving big data analysis, statistical analysis, and machine learning tech
 nologies and the interfaces by which users can transparently harness these
  techniques and technologies. \n\nThe primary responsibilities of this pos
 ition at TACC are the following:\n•	Explore and understand new techniques 
 and technologies related to support high performance scalable data analysi
 s and machine learning.  Responsible for assignments that require the tech
 nical knowledge to modify or adapt routine procedures under the direction 
 of a supervisor, to meet special research requirements for data projects h
 osted at TACC. \n•	Working with data providers, consumers, systems experts
 , and staff to design, develop, deploy, and support scalable high-performa
 nce machine learning application and systems at TACC. Assists fellow resea
 rch associates, research scientists, engineers, or faculty members with sp
 ecific phases of research projects and proposal preparation. \n•	Prepare u
 ser documentation and guides to support the usage and operations of data a
 nalysis tools and APIs supported and/or developed at TACC. Train and teach
  the capabilities and potential usages of machine learning techniques in a
  wide array of research domains and levels of computational abilities.\n•	
 Other related functions as assigned by manager and leadership team. \n\nRE
 QUIRED QUALIFICATIONS\nThe selected candidate must have the following mini
 mum qualifications:\n•	Bachelor’s degree or higher in Data Science, Comput
 er Science, Statistics, or other related research field with a strong back
 ground in machine learning and data analytics.\n•	Proficient in at least t
 wo of following programming languages: Python, Java and C++\n•	Knowledgeab
 le in data analysis software tools and environment, such as R, TensorFlow,
  Scikit-learn, pyTorch, and Spark.\n•	Working knowledge with website desig
 n, implementation and operation and familiar with HTML5, Java Script, and 
 web programming framework, \n•	The ability to learn, adapt, and teach new 
 technologies to enable new capabilities or improve on existing ones.\n•	Ex
 perience teaching data mining and machine learning to a wide array of stud
 ents, researchers, and developers.\n•	Excellent written and verbal communi
 cations skills.\n\nPREFERRED QUALIFICATIONS\nOne or more of the following 
 qualifications are strongly desired:\n•	Three or more years’ experience in
  developing and implementing machine learning algorithm/applications in an
  academic research environment.\n•	Experience implementing and supporting 
 a machine learning and data analytics applications, workflows.\n•	Practica
 l experiences with teaching, deploy and using at least one common deep lea
 rning frameworks such as Caffe, Tensorflow, Keras, PyTorch.\n•	Experience 
 developing applications in large parallel environments and tools such as H
 adoop, Hbase, HIVE, Elastic Search,  and SparkML. \n•	Familiar with standa
 rd parallel computing tools and interface, such as MPI, CUDA. \n•	Excellen
 t problem solving and strategic thinking skills.\n•	Recent peer-reviewed p
 ublications in computer science fields relevant to machine learning, big d
 ata analysis and/or high-performance computing.\n\nRegistration Category: 
 Tech Program Reg Pass, Workshop Reg Pass, Tutorial Reg Pass, Exhibits Reg 
 Pass
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