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Weekend Machine Learning Postdoc Jobs in Texas (NOW HIRING)

Tamus

Postdoctoral Researcher (CREDIT)

Prairie View, TX

$104.60K/yr

Job Title Postdoctoral Researcher (CREDIT) Agency Prairie View A&M University Department Electrical ... Perform research and design novel machine learning algorithms for Big Data analytics. * Develop ...

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX

$46.80K - $63.50K/yr

A postdoctoral fellowship position is available in the Department of Imaging Physics in the ... Experience with machine learning and deep learning techniques, mathematical modeling, or medical ...

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Weekend Machine Learning Postdoc information

What are the key skills and qualifications needed to thrive as a Weekend Machine Learning Postdoc, and why are they important?

To thrive as a Weekend Machine Learning Postdoc, you need a strong background in machine learning, statistics, and programming, typically supported by a PhD in a relevant field. Experience with tools such as Python, TensorFlow, PyTorch, and data analysis platforms, as well as familiarity with academic research methodologies, is essential. Exceptional problem-solving abilities, self-motivation, and effective communication are vital soft skills for success in research and collaboration. These skills enable you to drive innovative research, efficiently manage independent projects, and contribute meaningful insights to the field.

What are the typical projects and collaboration opportunities for a Weekend Machine Learning Postdoc?

As a Weekend Machine Learning Postdoc, you will often contribute to ongoing research projects, developing and refining machine learning models in collaboration with faculty, graduate students, and occasionally industry partners. While your hours are concentrated on weekends, you’ll typically participate in regular research meetings, code reviews, and may co-author papers or grant proposals. The role provides opportunities to mentor junior researchers and expand your expertise by working on interdisciplinary teams. This structure allows you to make significant research contributions while maintaining flexibility in your schedule.

What is a Weekend Machine Learning Postdoc?

A Weekend Machine Learning Postdoc is a postdoctoral researcher who focuses on machine learning projects and typically works on weekends or has a flexible schedule that includes weekend hours. This role often involves conducting advanced research in machine learning, developing algorithms, publishing papers, and collaborating with academic or industry teams. Weekend postdoc positions may be ideal for those balancing other commitments or seeking non-traditional work hours while continuing their research careers.

What is the difference between Weekend Machine Learning Postdoc vs Weekend Data Scientist?

AspectWeekend Machine Learning PostdocWeekend Data Scientist
Required CredentialsPhD in Computer Science, Machine Learning, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field
Work EnvironmentAcademic research settings, universities, research labsIndustry companies, startups, consulting firms
Employer & Industry UsageResearch institutions, universities, academic grantsTech companies, finance, healthcare, retail
Common Search & ComparisonYesYes

The Weekend Machine Learning Postdoc typically involves academic research with a focus on advancing machine learning theories and models, often requiring a PhD. In contrast, a Weekend Data Scientist applies data analysis and machine learning techniques in industry settings, often with a bachelor's or master's degree. Both roles may work on similar projects but differ mainly in their environment, credentials, and end goals.

What are the most commonly searched types of Machine Learning Postdoc jobs in Texas? The most popular types of Machine Learning Postdoc jobs in Texas are:
What are popular job titles related to Weekend Machine Learning Postdoc jobs in Texas? For Weekend Machine Learning Postdoc jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Weekend Machine Learning Postdoc jobs in Texas look for? The top searched job categories for Weekend Machine Learning Postdoc jobs in Texas are:
What cities in Texas are hiring for Weekend Machine Learning Postdoc jobs? Cities in Texas with the most Weekend Machine Learning Postdoc job openings:
Weekend Machine Learning Postdoc jobs near you
Postdoctoral Associate - AI for Brain Tumors

Postdoctoral Associate - AI for Brain Tumors

Baylor College of Medicine

Houston, TX • On-site

$62.23K/yr

Full-time

Posted 5 days ago

Baylor College of Medicine rating

8.6

Company rating: 8.6 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

49th of 529 rated colleges and universities

Job description

Job Title: Postdoctoral Associate - AI for Brain Tumors
Division: Neurosurgery
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 Postdoctoral Associate will develop next-generation AI models for large-scale perturbation modeling in brain tumors. The project will involve building and applying state-of-the-art machine learning approaches, including foundation models, variational autoencoders (VAEs), and transformer-based architectures, to integrate single-cell and multi-omic datasets. The goal is to decode tumor cellular heterogeneity and tumor microenvironment interactions, and to identify targetable genes, pathways, and therapeutic strategies at single-cell resolution.
Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates.
Job Duties
  • Develops and implements AI models for perturbation prediction:
    • Designs, trains, and evaluates machine learning models (e.g., transformer-based architectures, VAEs, and foundation models) to predict cellular responses to genetic and pharmacologic perturbations. This includes preprocessing large-scale single-cell and multi-omic datasets, defining model architectures, optimizing training pipelines on GPU clusters, and benchmarking against existing methods.
  • Integrate and analyze large-scale single-cell and multi-omic:
    • Processes and harmonizes scRNA-seq, scATAC-seq, and related datasets across brain tumor cohorts.
    • Performs downstream analyses such as cell state annotation, pathway enrichment, and tumor-tumor microenvironment interaction modeling to generate biologically meaningful insights.
  • Leads computational research projects and method development.
  • Performs other job-related duties as assigned.

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

Preferred Qualifications
  • Ph.D. in Computational Biology, Bioinformatics, Computer Science or a related quantitative field.
  • Strong background in machine learning and statistical modeling, with experience in deep learning frameworks (e.g., PyTorch or TensorFlow). Familiarity with modern architectures such as transformers, variational autoencoders (VAEs), and foundation models is highly desirable.
  • Experience in analyzing large-scale genomics or single-cell datasets (e.g., scRNA-seq, scATAC-seq).
  • Proficiency in Python and experience with R/Seurat or Scanpy.
  • Strong skills in writing efficient, reproducible, and well-documented code.
  • Evidence of productivity through first-author publications or preprints in computational biology, machine learning, or related fields.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.
PD; SN
Requisition ID: 24929

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