Careers

Positions Available:

 

Postdoctoral Researcher in Machine Learning for Hazards Management

The NSF-funded WIFIRE Commons project seeks to undertake convergence research on AI integrated wildland fire research and response, and to build a framework we call the WIFIRE Commons for using AI to enable innovative optimization of the evolving combinations of physics-based wildfire models and heterogeneous data sets used to monitor and predict wildfires in real-time.

The postdoc will work on projects to apply machine learning and artificial intelligence techniques for the detection, prevention, and management of hazards such as wildfires and floods. Research activities will involve analyzing large amounts of data from multiple data sources to understand and identify potential risks for various hazards. Approaches include statistical analysis, machine learning, deep learning, image processing, natural language processing, and risk analysis. The research will also require close collaboration with domain experts to establish a solid understanding of the data and conditions related to each hazard. Work will also involve implementing visualization techniques for displaying results; adding distributed processing capability to scale up analysis to large data sets; presenting results; and writing research papers.

Environment

The postdoctoral research will work as a part of the WIFIRE Lab (wifire.ucsd.edu) at the San Diego Supercomputer Center (SDSC.edu). SDSC is a leader and pioneer in high-performance and data-intensive computing, providing cyberinfrastructure resources, services, and expertise to the national research community, academia, and industry. Located on the UC San Diego campus, SDSC supports hundreds of multidisciplinary programs spanning a wide variety of domains, from astrophysics and earth sciences to disease research and drug discovery.

Duration

Funding is available for a 12 month position, with a high probability of renewed funding for extending the position.

COVID-19 Corollaries

Remote work is encouraged. Successful candidates can work remotely prior to arrival in San Diego, and will be expected to be ready to begin work immediately.

Qualifications

  • A PhD and extensive knowledge in scalable data analysis, machine learning, and deep learning techniques, demonstrated with publications and practical experience 
  • Familiarity with distributed big data frameworks and container technologies
  • Very strong Python programming skills
  • Geospatial and remote sensing experience highly desirable
  • Experience in hazards management is also highly desirable
  • Excitement about collaboration, working with multidisciplinary teams, and getting access to high-end computational systems and technology

Apply

Send CV, cover letter, research statement, and three references to Dr. Ilkay Altintas (ialtintas@ucsd.edu).

Deadline

Position is available immediately. Applicants will be considered until the position is filled. The hire will be expected to work primarily with Dr. Ilkay Altintas, but will be co-supervised by the senior members of the WIFIRE team.

Postdoctoral Researcher in Data Science Workflow and System Optimization

The TemPredict study was launched in March in response to the U.S. COVID-19 pandemic. To date, TemPredict has gathered continuous wearable data time series from ~50K individuals covering 2020, and has >1 million symptom survey responses from this cohort, giving symptom and diagnosis information as labels. Help develop appropriate data management, cleaning, and curation methods for large, real-world data sets, and help discover patterns from these data that can drive real-world deployment for disease alerts, public health management efforts, and future efforts of wearable data in biomedical research.

The postdoctoral researcher will interact as part of a team working on workflows to generate findings from TemPredict data, and to make TemPredict data securely accessible for collaborations. In particular, the postdoctoral researcher will: 

  • Investigate novel architectures and technologies for data management systems in the context of biomedical and wearable sensor data including deidentification, curation, modeling, integration and publishing of research datasets.
  • Develop workflow automation and performance optimization methods for integration of data building blocks with analytical environments and machine learning methods using scalable systems.
  • Research utilization of workflows for responsible, fair and ethical analysis of data.

Environment

The postdoctoral research will work as a part of the WorDS Center of Excellence (words.sdsc.edu) at the San Diego Supercomputer Center (SDSC.edu) and the Halıcıoğlu Data Science Institute (HDSI - datascience.ucsd.edu). SDSC is a leader and pioneer in high-performance and data-intensive computing, providing cyberinfrastructure resources, services, and expertise to the national research community, academia, and industry. Located on the UC San Diego campus, SDSC supports hundreds of multidisciplinary programs spanning a wide variety of domains, from astrophysics and earth sciences to disease research and drug discovery.  HDSI is a collaborative and innovative academic unit across multiple disciplines at UC San Diego. HDSI seeks to lay the groundwork for the scientific foundations of this emerging discipline, develop new methods and infrastructure, and train students, faculty and industrial partners to use data science in ways that will allow them to solve some of the world’s most pressing problems.

Duration

Funding is available for a 12 month position, with a high probability of renewed funding for extending the position.

COVID-19 Corollaries

Remote work is encouraged. Successful candidates can work remotely prior to arrival in San Diego, and will be expected to be ready to begin work immediately.

Qualifications

  • A PhD in the area of scientific computing and distributed computing techniques that relate to optimization of the discovery cycle using artificial intelligence. Equivalent expertise in a related area post-PhD is also acceptable.
  • A high degree of competence in data modeling, database systems, machine learning and distributed programming techniques and technologies.
  • Expert-level knowledge of python. Should be able to demonstrate competency or previous works for large data projects.
  • Excited about collaboration, working with multidisciplinary teams, and getting access to high-end computational systems and technology.
  • Excited about applications of technology to health and development of team science methodologies for problem solving at scale.

Apply 

Send CV, cover letter, research statement, and three references to Dr. Ilkay Altintas (ialtintas@ucsd.edu).

Deadline

Position is available immediately. Applicants will be considered until the position is filled. The hire will be expected to work primarily with Dr. Ilkay Altintas, but will be co-supervised by Prof. Benjamin Smarr. 

Postdoctoral Researcher in Workflows for Team Data Science

Our team (https://words.sdsc.edu/research) is looking for a motivated Postdoc. The preferred candidate will show demonstrable work experience in multi-objective optimization, in designing, development, and optimization of components in areas intersecting Scientific Workflows, Machine Learning and Deep Learning. The preferred candidate will have proven track record of using advanced computer science, data science, and HPC software research and development principles, in the domain of large-scale scientific workflows, to perform complex research, technology and software development.

The individual will be expected to resolve complex research and technology development and integration issues, and give technical presentations to associated research and technology groups. The preferred candidate will have experience-based evidence of evaluating new hardware and development of new software technologies for advancing complex High Performance Computing, Data Science, and Cyberinfrastructure projects. The preferred candidate will have experience of publishing and representing their team at national and international meetings, conferences and committees. The candidate will be expected to work with a team of research and technical staff.

The postdoc will interact with collaborators, to assess the data science and computational capabilities of its users; collaborate with scientific research faculty to develop both new research and novel data science applications that are maximally useful for workflow science research community. The preferred candidate will collaborate with other local and national online science data resources to optimize for interoperability with these centers; and interact with other Computer Science researchers in the field to incorporate or extend their research tools for our applications.

Qualifications

  • PhD. degree in Computer Science / Data Science, or Domain Sciences with computer / computational / data specialization or equivalent experience.
  • Interest, knowledge and proven experience with scientific and machine learning workflows
  • Demonstrable expertise in Machine Learning, Deep Learning, Optimization, Benchmarking, and preferably knowledge of one of these fields: HPC performance and power modeling, analyzing hardware, software, and applications for HPC.
  • Advanced knowledge of modeling and experience with multi-objective optimization, High Performance Computing, Data Science and CI.
  • Advanced experience working in a complex computing environments encompassing all or some of the following components: HPC, large-scale Data Science infrastructure and tools / software, and diverse domain science applications.
  • Self-motivated and works independently and as part of a team.
  • Track record of skills and experience in independently resolving complex computing / data / CI problems using introductory and / or intermediate principles.
  • Related work experience in assessing a broad spectrum of technical and research needs and demands and establish priorities, delegate and / or lead development of solutions to meet such needs.
  • Experience with the Kepler Workflow Management System will be preferred.

Apply

Please send your resume & cover letter for the position to Dr. Ilkay Altintas, with subject below:

Email: ialtintas@ucsd.edu

Subject: Application for PostDoc [ CSE - UCSD ]