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UID:submissions.supercomputing.org_SC23_sess503_job194@linklings.com
SUMMARY:Postdoctoral Research Associate - Machine Learning for Protein Des
 ign
DESCRIPTION:Overview: \n\nOak Ridge National Laboratory is the largest US 
 Department of Energy science and energy laboratory, conducting basic and a
 pplied research to deliver transformative solutions to compelling problems
  in energy and security. Our capabilities span a broad range of scientific
  and engineering disciplines, enabling the Laboratory to explore fundament
 al science challenges and to carry out the research needed to accelerate t
 he delivery of solutions to the marketplace.\n\n \n\nWe are seeking a Post
 doctoral Research Associate who will support the Biostatistics and Biomedi
 cal Informatics Group in the Computational Sciences and Engineering Divisi
 on, Computing and Computational Sciences Directorate at Oak Ridge National
  Laboratory (ORNL). The position will work as part of a crosscutting initi
 ative for Enzyme Engineering funded by the ORNL Director’s Research and De
 velopment Program. The Enzyme Engineering Initiative is developing a high-
 throughput Design-Build-Test-Learn pipeline for engineering enzymes that c
 atalyze reactions at materials interfaces.\n\n \n\nIn this position, you w
 ill work in a collaborative and interdisciplinary team with experimental a
 nd computational scientists to engineer proteins interacting with material
 s for plastics degradation, metal binding, and material synthesis. You wil
 l be expected to apply and develop machine learning approaches for protein
  design and to integrate these approaches with computational structural bi
 ology.\n\n \n\nMajor Duties/Responsibilities: \n\nPerform research in mach
 ine learning-guided protein design\nIntegrate experimental and simulation 
 data into machine learning workflows\nWork with the team to analyze and tr
 oubleshoot results and performance of machine learning models\nPresent and
  publish research findings in scientific conferences and peer-reviewed jou
 rnals\nParticipate in project planning and execution\nWork with staff to d
 evelop new proposals\nMaintain detailed and accurate records\nMaintain str
 ong dedication to the implementation and perpetuation of values and ethics
 \nDeliver ORNL’s mission by aligning behaviors, priorities, and interactio
 ns with our core values of Impact, Integrity, Teamwork, Safety, and Servic
 e. Promote diversity, equity, inclusion, and accessibility by fostering a 
 respectful workplace – in how we treat one another, work together, and mea
 sure success.\n \n\nBasic Qualifications:\n\nA PhD in computational biophy
 sics, chemistry, biology, or a related field completed within the last 5 y
 ears\nStrong background in protein sequence analysis, structural modeling,
  and machine learning\nDemonstrated ability to program in Python\n \n\nPre
 ferred Qualifications:\n\nExperience with protein engineering and computat
 ional protein design\nExperience with large language models\nExperience wi
 th machine learning frameworks such as PyTorch, TensorFlow, and Scikit-lea
 rn\nProven publication record\nExcellent written and oral communication sk
 ills\nMotivated self-starter with the ability to work independently and to
  participate creatively in collaborative teams across the laboratory \nAbi
 lity to function well in a fast-paced research environment, set priorities
  to accomplish multiple tasks within deadlines, and adapt to ever changing
  needs\n \n\nFor additional information, please contact Dr. Serena Chen (c
 hens@ornl.gov).\n\n \n\nPlease submit three letters of reference when appl
 ying to this position. You can upload these directly to your application o
 r have them sent to postdocrecruitment@ornl.gov with the position title an
 d number referenced in the subject line.\n\n \n\nInstructions to upload do
 cuments to your candidate profile:\n\nLogin to your account via jobs.ornl.
 gov\nView Profile\nUnder the My Documents section, select Add a Document\n
  \n\nApplicants cannot have received their Ph.D. more than five years prio
 r to the date of application and must complete all degree requirements bef
 ore starting their appointment. The appointment length will be for up to 2
 4 months with the potential for extension. Initial appointments and extens
 ions are subject to performance and the availability of funding.\n\n \n\nM
 oving can be overwhelming and expensive. UT-Battelle offers a generous rel
 ocation package to ease the transition process. Domestic and international
  relocation assistance is available for certain positions. If invited to i
 nterview, be sure to ask your Recruiter (Talent Acquisition Partner) for d
 etails.\n\n
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