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System Engineer Phd Jobs in Tyler, TX (NOW HIRING)

micro1 AI

Bioinformatics Software Engineer

Tyler, TX · Remote

$80 - $110/hr

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will ... advanced degree (PhD, MSc, PharmD) highly valued but not strictly required. * Strong coding ...

micro1 AI

AI Training Specialist - Life Sciences

Tyler, TX · Remote

$90 - $120/hr

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will ... Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry ...

micro1 AI

Digital Chemistry Specialist - Remote

Tyler, TX · Remote

$90 - $120/hr

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will ... Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry ...

micro1 AI

Director of Biostatistics

Tyler, TX · Remote

$60 - $100/hr

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will ... MS or PhD in biostatistics, statistics, or epidemiology. * 4+ years of experience in pharmaceutical ...

micro1 AI

Director of Biostatistics

Tyler, TX · Remote

$60 - $65/hr

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will ... Advanced degree (MSc or PhD) in Biostatistics, Statistics, or a closely related quantitative field.

All JobsSystem Engineer Phd JobsSystem Engineer Phd Jobs in Tyler, TX

System Engineer Phd information

See Tyler, TX salary details

$50.4K

$119.9K

$157.4K

How much do system engineer phd jobs pay per year?

As of Aug 16, 2026, the average yearly pay for system engineer phd in Tyler, TX is $119,878.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,300.00 and $147,900.00 per year, depending on experience, location, and employer.

What are common challenges system engineer PhDs face when transitioning from academia to industry roles?

System Engineer PhDs often encounter challenges when shifting from academic research to industry, such as adapting to faster project timelines and working within cross-functional teams. In industry, there is typically a greater emphasis on practical application and collaboration, rather than theoretical exploration. Adjusting to structured workflows and aligning technical solutions with business objectives are also key transitions. However, this environment offers opportunities to see the tangible impact of your work and to advance into senior technical or leadership roles.

What is the difference between System Engineer Phd vs Network Engineer?

AspectSystem Engineer PhdNetwork Engineer
Required CredentialsPhd in Engineering or related field, possibly with certifications like Cisco or CompTIAAssociate's or Bachelor's in Computer Science or related, with certifications like Cisco CCNA or CCNP
Work EnvironmentResearch labs, R&D departments, or advanced technical teams in tech companiesNetwork operations centers, IT departments, or telecommunications firms
Employer & Industry UsageResearch institutions, tech companies, or organizations requiring advanced system designTelecom providers, enterprise IT, or service providers

The main difference between a System Engineer Phd and a Network Engineer lies in their focus and qualifications. System Engineers with a Phd typically engage in advanced system design, research, and development, often in research or high-tech environments. Network Engineers focus on designing, implementing, and maintaining network infrastructure, usually with industry certifications. Both roles are essential in tech industries but serve different technical needs and expertise levels.

What are the key skills and qualifications needed to thrive as a system engineer PhD, and why are they important?

To thrive as a System Engineer PhD, you need advanced knowledge of systems engineering principles, research methodologies, and typically a doctorate in engineering or a related field. Familiarity with modeling and simulation tools (e.g., MATLAB, Simulink), systems engineering software (e.g., IBM DOORS), and relevant industry certifications are highly valuable. Strong analytical thinking, problem-solving abilities, and effective communication skills help you lead complex projects and collaborate with multidisciplinary teams. These skills and qualifications are essential for driving innovation, ensuring robust system design, and successfully managing sophisticated engineering challenges.

What is a system engineer PhD?

System Engineer PhDs are professionals who have earned a doctoral degree (PhD) in systems engineering or a closely related field. They specialize in designing, analyzing, and managing complex systems across various industries, such as aerospace, defense, IT, and manufacturing. Their advanced education enables them to conduct research, develop innovative solutions, and lead multidisciplinary teams to tackle large-scale engineering challenges. System Engineer PhDs often work in academia, research institutions, or high-level industry roles, focusing on optimizing system processes and integration.

What can I do with a PhD in system engineer?

A PhD in system engineering prepares individuals for advanced roles in research, development, and systems design across industries such as aerospace, defense, technology, and manufacturing. Graduates often work as systems engineers, research scientists, or technical consultants, utilizing skills in systems analysis, modeling, and simulation, and may pursue careers in academia or industry innovation.

What are popular job titles related to System Engineer Phd jobs in Tyler, TX?

For System Engineer Phd jobs in Tyler, TX, the most frequently searched job titles are:

What cities near Tyler, TX are hiring for System Engineer Phd jobs?

Cities near Tyler, TX with the most System Engineer Phd job openings:

System Engineer Phd jobs near you

Bioinformatics Software Engineer

micro1 AI

Tyler, TX • Remote

$80 - $110/hr

Part-time

Posted 13 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

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