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Remote Machine Learning Postdoc Jobs in Texas (NOW HIRING)

Sr/Staff Data Scientist (Remote - US)

TX · On-site +1

$165K - $300K/yr

Remote US Anticipated Start Date: 06/01/2026 The US base salary range for this full-time position ... Lead the development and deployment of advanced machine learning models to forecast outcomes and ...

From downtown hotels and luxury resorts to private vacation rentals and remote cabins, Vogo offers ... This role will own the Machine Learning models that drive our business from development to ...

Data Scientist

Richardson, TX · Remote

$116.40K - $198.20K/yr

Machine Learning & Data Science * Develop, evaluate, and deploy predictive and generative models ... Experience building AI solutions that support customer facing products #LI-REMOTE #LI-JL1 Physical ...

Data Scientist

Richardson, TX · Remote

$116.40K - $198.20K/yr

Responsibilities Machine Learning & Data Science * Develop, evaluate, and deploy predictive and ... Experience building AI solutions that support customer facing products #LI-REMOTE #LI-JL1 Physical ...

... remote within a mutually acceptable location. #LI-Hybrid Success Looks Like: * AI systems move ... Develop and deploy machine learning and generative AI solutions that support enterprise use cases.

Perform remote data collection, cleaning, transformation, and analysis * Apply statistical methods and machine learning techniques to datasets * Develop visualizations and dashboards using Tableau ...

This position is remote and requires a Secret clearance or higher. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

Perform remote data collection, cleaning, transformation, and analysis * Apply statistical methods and machine learning techniques to datasets * Develop visualizations and dashboards using Tableau ...

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Remote Machine Learning Postdoc information

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

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.

What is a Remote Machine Learning Postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.
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 cities in Texas are hiring for Remote Machine Learning Postdoc jobs? Cities in Texas with the most Remote Machine Learning Postdoc job openings:
Postdoctoral Fellow - Bioinformatics & Computational Biology

Postdoctoral Fellow - Bioinformatics & Computational Biology

MD Anderson

Houston, TX • On-site, Remote

$64K - $76K/yr

Other

Medical, Dental, Retirement, PTO

Posted 9 days ago


MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 163 frontline employees who took The Breakroom Quiz

31st of 864 rated healthcare providers


Job description

A full-time postdoctoral fellow position is available in Dr. Ye Zheng's lab at the Department of Bioinformatics and Computational Biology, the University of Texas MD Anderson Cancer Center. We are seeking a highly motivated and dedicated postdoctoral researcher to join our dynamic, hybrid, and highly collaborative lab.

This computational postdoctoral fellow candidate is expected to leverage single-cell/bulk-cell multi-omics, spatial omics, and pathological imaging data to reveal the cancer-specific mechanisms underlying the differential efficacies and toxicities of treatments across patients. This position offers an exciting opportunity to contribute to pioneering biological, clinically important and methodologically challenging problems by innovating cutting-edge statistical models, computational methods and AI agent skills. This position provides extensive training in grant writing, with a focus on prestigious early career development grants such as the K99 and Damon Runyon awards.

Dr. Zheng's lab works on problems at the interface of statistical, computational and biomedical sciences. The lab has developed methods to decipher gene cis-regulatory mechanisms from transcriptomics, epigenomics, proteomics and three-dimensional (3D) chromatin interaction perspectives.

All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations. LEARNING OBJECTIVES The postdoctoral fellow will achieve the following learning goals: (1) develop rigorous and reproducible statistical and machine learning methods for integrating multi-modality cancer datasets, with strong benchmarking and uncertainty awareness, and deliver these methods as well documented computational tools; (2) build AI pathology models that convert tissue morphology into quantitative features to support downstream molecular interpretation, including deconvolution and harmonization approaches for robust comparison across patients, cohorts, and tissue types; (3) create agentic AI workflows that automate analysis from data ingestion and quality control to interpretation and report generation, with emphasis on transparency, auditability, and scalability on high performance computing systems; (4) conduct integrative modeling of 3D genome organization and cross platform cell surface protein measurements to improve gene regulation insight and cell type and state characterization; (5) develop professional skills through structured mentorship in manuscript writing, scientific communication, and career development applications, including K99 R00 and Damon Runyon. ELIGIBILITY REQUIREMENTS Candidates with a Ph.D

in Computer Science, Statistics, Biostatistics, Bioinformatics, Computational Biology, Engineering, Data Science, or a related field are encouraged to apply. 1. Solid training in statistics and mathematics: Past course or research training in statistics, including but not limited to mathematical statistics, statistical inference, and linear regression.

2. Strong computational skills: Proficient in developing computational tools and modern AI agent-related workflows. Proficient in programming languages R, Python, and Shell, has extensive experience in using high-performance computing environments on Linux servers, and knows how to submit batch-run jobs.

Experienced in processing and analyzing bulk/single-cell genomic data, spatial omics data, or image data. Ability to conduct highly organized and reproducible research. 3.

Genomics knowledge: Have experience working on genetic or genomic data. Can interpret the biological findings. 4.

Strong communication, writing, and collaboration ability. 5. First, co-first, corresponding, or co-corresponding publications and reprints under review on computational and/or statistical methodology development are required to demonstrate academic writing ability.

ADDITIONAL APPLICATION INFORMATION Lab website and potential research project descriptions: https://compbiowizard.github.io./ To apply, please email the following to Dr. Ye Zheng at yzheng8@mdanderson.org. (1) a cover letter describing past contributions to the field, future research plan, career development plan, scientific motivation and interests that align with Dr

Zheng's lab, (2) a curriculum vitae that includes publications and GitHub links to past project codes or developed software (3) emails and phone numbers of a list of three references POSITION INFORMATION MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000. depending on the number of years of postgraduate experience. The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.

This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment. It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law

http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html Apply


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