1

Evolutionary Computing Jobs in Texas (NOW HIRING)

Senior Compiler Engineer - AI

Austin, TX · On-site

$121K - $160K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... learning, genetic/evolutionary algorithms, predictive modeling, complex systems, and high ...

Senior Compiler Engineer - AI

Austin, TX · On-site

$121K - $160K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... Deep familiarity with reinforcement learning, genetic/evolutionary algorithms, predictive modeling ...

Senior Compiler Engineer - AI

Austin, TX

$121K - $160K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... Deep familiarity with reinforcement learning, genetic/evolutionary algorithms, predictive modeling ...

Evolutionary Computing information

What is evolutionary computing?

Evolutionary computing is a branch of artificial intelligence that uses algorithms inspired by the process of natural selection to solve complex optimization and search problems. These algorithms, such as genetic algorithms, evolve solutions over time by mimicking biological mechanisms like mutation, crossover, and selection. Evolutionary computing is used in various fields, including engineering, economics, and robotics, to find solutions that might be difficult to obtain through traditional methods. It is especially useful for problems where the search space is vast and not easily navigable by conventional algorithms.

What are the key skills and qualifications needed to thrive as an evolutionary computing specialist?

To thrive as an Evolutionary Computing Specialist, you need a solid background in computer science, mathematics, and algorithm design, often supported by an advanced degree in a related field. Familiarity with programming languages (such as Python, C++, or Java), machine learning frameworks, and optimization libraries is typically required. Strong analytical thinking, problem-solving abilities, and creativity are crucial soft skills that help in developing innovative solutions. These skills enable specialists to design and implement effective evolutionary algorithms that solve complex computational problems across various domains.

What are some common challenges faced when implementing evolutionary computing algorithms in real-world projects?

One of the main challenges in applying evolutionary computing algorithms is balancing computational cost with solution quality, as these algorithms can be resource-intensive and require careful parameter tuning. Additionally, translating theoretical models into scalable, real-world applications often involves customizing operators and fitness functions to suit specific domains. Collaboration with domain experts is crucial to accurately define objectives and constraints, and ongoing communication with software engineers ensures efficient integration into existing systems.

What is the difference between Evolutionary Computing vs Data Scientist?

AspectEvolutionary ComputingData Scientist
Required CredentialsTypically a degree in computer science, AI, or related fields; certifications in AI or machine learningDegree in statistics, computer science, or related fields; certifications in data analysis or machine learning
Work EnvironmentResearch labs, AI development teams, academiaBusiness environments, tech companies, consulting firms
Industry UsageOptimization problems, evolutionary algorithms researchData analysis, predictive modeling, business insights
Common Search/ComparisonYesYes

While both roles involve advanced computing techniques, Evolutionary Computing focuses on algorithms inspired by natural selection for optimization, whereas Data Scientists analyze data to extract insights and build predictive models. They often collaborate but serve different primary functions within tech and research industries.

Postdoctoral Associate - BioSciences

Rice University

Houston, TX

$55K - $60K/yr

Full-time

Re-posted 16 days ago


Rice University rating

8.2

Company rating: 8.2 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

149th of 627 rated colleges and universities


Job description

Position Summary:
Dr. Lauren Hennelly's lab in the Department of Biosciences seeks to hire a Postdoctoral Research Associate in the field of Evolutionary and Conservation Genomics.

The Hennelly Lab is hiring a Postdoctoral Research Associate in evolutionary and population genomics in mammalian systems. The project will involve analyzing genomic data from modern and historical/ancient genomic datasets, and using computational methods to assess patterns and evolutionary consequences of hybridization between different canid species. The initial contract is 1 year and renewable for 1 extra year.

Our lab studies the evolutionary processes that shape genetic and phenotypic variation in animals. We integrate population genomic data, museum and ancient DNA, fieldwork, and phenotypic data to investigate the evolutionary histories of species, how anthropogenic change alters evolutionary trajectories of species, and the molecular basis of complex and adaptive traits (https://hennellylab.com/).


Special Instructions to Applicants:
All interested applicants should attach a resume in the Supporting Documents section of the application, preferably in a PDF format to avoid any formatting issues.


All interested applicants should apply through the job posting and also email the following materials to Dr. Lauren Hennelly at lh106@rice.edu:

  • A one-page cover letter describing their research experience, career goals, and interest in the position

  • CV

  • Contact information for three references

Ideal Candidate Statement:
The ideal candidate will be a highly motivated postdoctoral research associate with strong experience in computational and bioinformatic methods, population genomic analysis, and an interest in addressing fundamental questions in evolutionary biology, including speciation, adaptation, and consequences of hybridization in mammalian systems. The postdoctoral researcher will have opportunities to collaborate with researchers, external collaborators, and PhD students in the Hennelly Lab. The position is designed to support the candidate's professional development through opportunities in scientific publishing, grant writing, student mentorship, and scientific outreach.

Workplace Requirements: 

In-person work in Houston is preferred. However, we offer the flexibility of hybrid or fully remote work. Please note that fully remote eligibility is limited to residents of approved states. Hybrid roles integrate on-campus and remote work to foster both independence and collaboration. In accordance with Rice Policy 440, work arrangements are subject to periodic review and adjustment.

Annual Hiring Range:  $55,000-$60,000
*Exempt (salaried) positions under FLSA are not eligible for overtime. 

This position is funded by a grant, soft and/or restricted funds. Continued employment is contingent on the renewal of funding.

Essential Functions

  • Design and conduct research in evolutionary and population genomics analyses using large whole genome datasets

  • Analyze genomic datasets (inferring local ancestry, population structure, phylogenomics, patterns of hybridization), data interpretation, prepare manuscripts for peer-reviewed publications, and present research findings at scientific conferences and seminars. 

  • Opportunities to mentor and/or train junior research team members, including undergraduate and graduate students in computational and genomic research methods. 

  • Assist with coordination of permitting procedures and logistics of sample collection. 

  • Contribute to a collaborative and supportive environment and ongoing research activities in the lab. 

Required Qualifications and Skills

  • Ph.D. in evolutionary biology, genomics, ecology, genetics, or related field by the start date 

  • Research background in population genomics, evolutionary genomics, conservation genomics, or related field

  • Knowledge of analyzing large-scale genomic datasets

  • Proficiency with computational and bioinformatic approaches for genomic data analysis, such as using R, slurm, on a Linux/Unix computing cluster

  • Knowledge of population genetic and evolutionary theory and its application to genomic data

  • Strong organizational and data-management skills

  • Excellent written and verbal communication skills, including ability to communicate research findings through scientific publications and presentations

  • Ability to work independently and collaboratively while contributing to a supportive, interactive research environment

Preferred Qualifications (optional)

  • Experience or interested in learning data analysis of degraded DNA genomic datasets from museum specimens, experience conducting analyses to study hybridization, introgression, and inferring demographic histories.

Rice University HR | Benefits: https://knowledgecafe.rice.edu/benefits 
Rice Mission and Values: Mission and Values | Rice University 

Rice University is committed to ensuring Equal Employment Opportunity and welcoming the fullness of diversity into our candidate pools. Rice considers qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national or ethnic origin, genetic information, disability, or protected veteran status. Rice also provides reasonable accommodations to qualified persons with disabilities. If an applicant requires a reasonable accommodation for any part of the application or hiring process, please get in touch with Rice University's Human Resources Office via email at facstaffada@rice.edu for support.

If you have any additional questions, please email us at jobs@rice.edu . Thank you for your interest in employment with Rice University.


What Rice University employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom