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Phd Translation information

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$27.5K

$57.2K

$87.5K

How much do phd translation jobs pay per year?

As of Jul 7, 2026, the average yearly pay for phd translation in the United States is $57,200.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,000.00 and $57,500.00 per year, depending on experience, location, and employer.

What is a PhD in Translation?

A PhD in Translation is a doctoral degree focused on advanced research in translation studies, including theory, methodology, and practice. Students in this program typically explore topics such as translation theory, intercultural communication, linguistics, and the use of technology in translation. Graduates often pursue academic careers, research positions, or leadership roles in translation and localization industries. The degree usually requires original research culminating in a dissertation that contributes new knowledge to the field.

What are typical research and collaboration opportunities for a PhD in Translation within academic or professional settings?

PhD holders in Translation often engage in interdisciplinary research, working alongside linguists, literary scholars, or experts in technology to explore new translation theories or tools. Collaborative projects may include co-authoring papers, participating in international conferences, or consulting on large-scale translation initiatives. These roles frequently involve mentoring graduate students, contributing to curriculum development, and building partnerships with industry or translation agencies. Such collaboration not only enriches research but also opens pathways to leadership or specialized academic positions.

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

To thrive as a PhD-level Translator, you need advanced proficiency in at least two languages, deep subject-matter expertise, and a doctoral degree in translation studies or a related field. Familiarity with computer-assisted translation (CAT) tools, terminology databases, and research methodologies is typically required. Exceptional attention to detail, cultural sensitivity, and strong analytical and communication skills distinguish top performers in this role. These abilities ensure accurate, contextually appropriate translations and contribute to academic or professional credibility.

What is the difference between Phd Translation vs Translator?

AspectPhd TranslationTranslator
Required CredentialsPhD in Translation, Linguistics, or related fieldTypically a bachelor's or master's degree, certification optional
Work EnvironmentAcademic, research, or specialized industry settingsFreelance, corporate, or agency-based translation work
Industry UsageAcademic publishing, research projects, specialized industriesBusiness, legal, medical, technical, general translation

While both roles involve language skills, a Phd Translation usually requires advanced academic credentials and focuses on research or specialized fields. A Translator may have less formal education but is more involved in day-to-day translation tasks across various industries.

More about Phd Translation jobs
What cities are hiring for Phd Translation jobs? Cities with the most Phd Translation job openings:
What states have the most Phd Translation jobs? States with the most job openings for Phd Translation jobs include:
What job categories do people searching Phd Translation jobs look for? The top searched job categories for Phd Translation jobs are:
Phd Translation jobs near you
Infographic showing various Phd Translation job openings in the United States as of July 2026, with employment types broken down into 86% Full Time, 8% Part Time, and 6% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $57,200 per year, or $27.5 per hour.
Data Scientist - Innovation - PhD (Irving, TX)

Data Scientist - Innovation - PhD (Irving, TX)

Caris Life Sciences

Irving, TX • On-site

Full-time

Posted 27 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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