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Phd Python Jobs in Dallas, TX (NOW HIRING)

Photon

Machine Learning Engineer - NJ

Addison, TX

$54 - $71.50/hr

... Python, Spark, and Databricks. Key Responsibilities: Analytics Model Development: * Analyze use ... A PhD is preferred but not necessary. * Experience: * At least 5 years of experience in data ...

Photon

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

... Python, Spark, and Databricks. Key Responsibilities: Analytics Model Development: * Analyze use ... A PhD is preferred but not necessary. * Experience: * At least 5 years of experience in data ...

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Phd Python information

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$22.8K

$138.5K

$200.3K

How much do phd python jobs pay per year?

As of Jul 13, 2026, the average yearly pay for phd python in Dallas, TX is $138,464.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,300.00 and $162,700.00 per year, depending on experience, location, and employer.

What Python jobs are in-demand?

Python developers are in high demand across industries such as technology, finance, healthcare, and data science. Common roles include data scientist, machine learning engineer, backend developer, and automation engineer, often requiring knowledge of frameworks like Django or Flask and proficiency in data analysis tools. These positions typically value strong programming skills, problem-solving ability, and experience with cloud platforms and version control systems.

Can we do PhD in Python?

A PhD in Python typically refers to research involving Python programming language, often in fields like computer science, data science, or artificial intelligence. While there is no formal PhD in Python itself, students pursue doctoral degrees in related areas and use Python as a primary tool for research and development. Earning a PhD requires completing original research, coursework, and a dissertation in a relevant field, with proficiency in Python being a valuable skill for data analysis, machine learning, and software development.

What are the key skills and qualifications needed to thrive as a PhD-level Python Developer, and why are they important?

To thrive as a PhD-level Python Developer, you need advanced programming skills in Python, a relevant doctoral degree (typically in computer science, data science, or a related field), and a strong foundation in research methodologies. Experience with scientific computing libraries (such as NumPy, pandas, and SciPy), machine learning frameworks, and version control systems like Git is highly valued. Exceptional problem-solving abilities, clear communication, and the capacity to work independently are crucial soft skills for this role. These skills and qualities are essential for driving innovative research, developing robust code, and effectively collaborating within interdisciplinary teams.

What types of collaborative projects might a PhD with Python expertise typically engage in within a research or industry setting?

PhDs with strong Python skills often work on multidisciplinary projects that require data analysis, machine learning, or automation. They may collaborate with domain experts, data scientists, and software engineers to design experiments, develop analytical tools, or build scalable research prototypes. Collaborative work frequently involves contributing to codebases, sharing insights through data visualization, and participating in regular meetings to align project goals. Such environments foster both technical growth and exposure to diverse fields, supporting career advancement through impactful contributions.

Is Python in high demand?

Python is in high demand across many industries, especially for roles involving data analysis, machine learning, web development, and automation. Python developers with skills in frameworks like Django or Flask and experience with libraries such as Pandas or TensorFlow are highly sought after in the job market.

What is the highest paying job in Python?

The highest paying jobs involving Python typically include roles such as Machine Learning Engineer, Data Scientist, and Quantitative Analyst, often requiring advanced skills in algorithms, statistics, and frameworks like TensorFlow or PyTorch. These positions can offer salaries exceeding $150,000 annually, especially with experience, certifications, and work in finance, tech, or research environments.

What is a PhD Python developer?

A PhD Python developer is a professional who has earned a Doctor of Philosophy (PhD) degree and specializes in using the Python programming language for research, data analysis, software development, or academic projects. These individuals often work in fields like data science, machine learning, scientific computing, or academia, where complex problem-solving and advanced analytical skills are required. Their expertise in both research methodologies and Python allows them to tackle sophisticated computational tasks and contribute to cutting-edge innovation.
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Phd Python jobs near you
Infographic showing various Phd Python job openings in Dallas, TX as of July 2026, with employment types broken down into 33% Full Time, and 67% Contract. Highlights an 100% In-person job distribution, with an average salary of $138,464 per year, or $66.6 per hour.
Data Scientist - Innovation - PhD (Irving, TX)

Data Scientist - Innovation - PhD (Irving, TX)

Caris Life Sciences

Irving, TX • On-site

Full-time

Re-posted 3 days ago

Job description

Job Summary:
Caris Life Sciences is transforming cancer care through precision medicine and cutting-edge molecular science. As a Data Scientist on the Innovation Team, you will develop machine learning and deep learning algorithms on molecular sequencing data to improve cancer diagnostics and treatment.
Responsibilities:
• Processing, manipulating, and analyzing large diverse datasets generated from NGS to develop biomarkers for cancer diagnosis, prognosis, and treatment.
• Developing novel algorithms for feature extraction and biomarker discovery from molecular sequencing data.
• Applying first-principles analysis to translate open research questions into tractable, well-defined problems.
• Applying state-of-the-art machine learning and deep learning methods to biological and clinical research questions.
• Creating rigorous evaluation frameworks and tracking experiments systematically using tools such as MLflow or Weights & Biases.
• Authoring peer-reviewed research publications and presenting findings at scientific conferences.
Qualifications:
Required:
• PhD in Data Science, Bioinformatics, Computational Biology, Genomics, Statistics, Computer Science, Engineering, Biophysics, or a related quantitative or biological field.
• PhD recently completed, or up to approximately 2 years of post-doctoral research experience (academic or industry).
• Demonstrated work on a cancer biology or translational research problem (PhD thesis chapter, peer-reviewed publication, or postdoc / industry role).
• Hands-on experience with molecular sequencing data (e.g., WGS, WES, RNA-seq, cfDNA) including production-grade pipelines and analysis.
• Hands-on experience with generative AI -- large language models, foundation models (e.g., genomic or protein language models), or agentic workflows applied to scientific or clinical data.
• Proficiency with PyTorch and modern deep learning architectures (transformers, attention mechanisms), with demonstrated application of ML/DL to biological or clinical data.
• First-author or co-first-author peer-reviewed publications in machine learning venues (e.g., NeurIPS, ICML, ICLR) or in bioinformatics / computational biology journals.
• Strong Python; comfortable in Linux; proficient with git and collaborative workflows.
Preferred:
• Multi-omics integration experience (genomics, transcriptomics, proteomics, methylation, etc.).
• Experience with epigenetics -- DNA methylation analysis, chromatin biology, or related.
• Interest in cell-free DNA, liquid biopsy, and next-generation early cancer diagnostics.
• Interest in novel algorithm development for biomedical signal extraction in sequencing data.
• Proficiency in cloud platforms (AWS EC2, S3, HealthOmics) and containerization (Docker).
Company:
Caris Life Sciences develops molecular profiling and AI-driven technologies to support precision medicine in oncology. Founded in 2008, the company is headquartered in Irving, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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