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Postdoc In Topological Data Jobs in Texas (NOW HIRING)

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Postdoctoral Research Associate

College Station, TX

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... in which students use environmental sensors, real-world data, and carefully designed AI-supports to ... The postdoctoral research associate will join an interdisciplinary, multi-site research-practice ...

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Postdoc In Topological Data information

What is a postdoc in topological data?

A Postdoc in Topological Data is a researcher who has completed their PhD and is engaged in advanced research focused on the application of topology—an area of mathematics dealing with spatial properties—to analyze and interpret complex data sets. These positions typically involve both theoretical work and the development of computational tools to extract meaningful patterns from high-dimensional or complex data. Postdocs in this field often collaborate with interdisciplinary teams in mathematics, computer science, and applied domains such as biology or engineering. The role is intended to deepen expertise, publish research, and prepare for academic or research-intensive careers.

What are the key skills and qualifications needed to thrive as a postdoc in topological data?

To thrive as a Postdoc in Topological Data, you need a strong background in mathematics (particularly topology, algebra, and geometry), data analysis, and a PhD in a related field. Familiarity with computational tools like Python, R, MATLAB, and software libraries for topological data analysis (such as GUDHI or Ripser) is typically required. Exceptional problem-solving ability, collaboration, and strong scientific communication skills help distinguish top candidates in interdisciplinary research environments. These skills are crucial for advancing research, publishing high-quality work, and contributing effectively to collaborative scientific projects.

What are some typical collaborative opportunities for a postdoc in topological data within academic or research settings?

As a Postdoc in Topological Data, you can expect to collaborate closely with interdisciplinary teams, including mathematicians, computer scientists, and domain experts from fields like biology or materials science. Collaborative projects often involve developing or applying topological methods to analyze complex datasets, contributing both theoretical insights and computational tools. These interactions may include co-authoring research papers, participating in joint seminars, and working with graduate students. Such collaborations not only broaden your research impact but also help expand your professional network and skill set.

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Postdoc In Topological Data jobs near you

Postdoctoral Associate - Cancer Epidemiology

Baylor College of Medicine

Houston, TX • On-site

$62K/yr

Full-time

Re-posted 23 days ago

Baylor College of Medicine rating

8.0

Company rating: 8.0 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

188th of 619 rated colleges and universities

Job description

Postdoctoral Associate - Cancer Epidemiology
Division: Medicine
Work Arrangement: Onsite only
Location: Houston, TX
Salary Range: $62,232
FLSA Status: Exempt
Work Schedule: Monday - Friday, 8 a.m. - 5 p.m.
Summary
The Section of Epidemiology and Population Sciences at Baylor College of Medicine invites applications for a Postdoctoral Associate position for our Cancer Epidemiology with Real-World Data (RWD) Training Program. The Training Program provides epidemiology and bioinformatics Postdoctoral Associates with training in how to combine traditional epidemiologic research methods with RWD and modern technologies, like artificial intelligence and natural language processing, for impactful cancer research. Exciting opportunities also exist to work with faculty from MD Anderson Cancer Center, Rice University and UTHealth School of Biomedical Informatics.
Job Duties
  • Analyzes large data sets.
  • Analyzes next generation sequencing data (e.g., RNA-seq, whole genome/ exome sequencing) to address complex biological and translational research questions.
  • Uses state-of-the-art bioinformatical and statistical tools
  • Develops new statistical methods to answer biological questions that arise in the research.
  • Prepares manuscripts, abstracts, and presentations for peer-reviewed journals and scientific conferences.
  • Ensures compliance with institutional, sponsor and data security guidelines for handling sensitive genomic and clinical data.
  • Conducts advanced analysis of large-scale biomedical and population health datasets to support ongoing research within the section.
  • Collaborates with multidisciplinary teams, including faculty investigators, statisticians, clinicians, and trainees, in a highly team-oriented research environment.
  • Participates in the Section's sponsored training program by contributing to collaborative projects, mentoring trainees, and engaging in programmatic activities such as seminars, workshops, and collaborative research initiatives.
  • Develops methodologies and tools for use in the electronic medical records that will strengthen the Learn Health System and improve patient outcomes.

Minimum Qualifications
  • MD or Ph.D. in Basic Science, Health Science, or a related field.
  • No experience required.

Preferred Qualifications
  • Ph.D. in Epidemiologists or Bioinformaticians or M.D.s/DVMs with related experience.
  • Has the ability to work in a team environment.
  • Experience with next generation sequencing data analysis is a plus.
  • Knowledge in cancer biology or genetics is preferable.
  • Excellent writing skills in English.

Requisition ID: 25833

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