Post-Doctoral Fellow

Job Summary:

We are searching for a qualified post-doctoral fellow to join our growing laboratory, whose principal investigator is an NIH-funded researcher. This individual will conduct interdisciplinary and highly collaborative research in ovarian cancer to predict clinically relevant tumor features. The researcher will work on large and diverse molecular datasets, primarily consisting of bulk and single-cell transcriptomic data. The candidate should be proficient in, or highly motivated to learn cancer data science, machine learning, and high throughput sequencing analysis. Successful applicants will need to work both independently and collaboratively, to exhibit excellent skills in scientific communication, and dedicated to scientific reproducibility, replicability, and transparency.

Key Responsibilities:

(Specific Position Duties with percentages of time)

Research (85-90%)

• Data management
• Code maintenance, documentation, and review
• Designing and performing computational experiments
• Developing and validating new computational methodologies/applications relevant to the research

Administrative (5-10%)

• Writing full-length, high-quality scientific publications
• Presenting research at national and international scientific meetings
• Developing grant-writing skills by applying for institutional or other small grants

Teaching (5%)

• Teach/supervise students or junior research services professionals 

Work Location:

Onsite - this role is expected to work onsite and is located in Aurora, CO.  

Why Join Us:

The Department of Obstetrics and Gynecology at the University of Colorado is a world-class research enterprise, ranked 17th in the nation by the Blue Ridge Institute for federal funding. The Department currently has an impressive research portfolio of $32M in existing federal and foundation grants and contracts through the lifetime of the projects, increasing in budget annually by $9M. Departmental faculty provide a full-spectrum of clinical care for women of all ages, participate in research, and provide education to students and residents.

The University of Colorado offers a comprehensive benefits package that includes health insurance, life insurance, retirement plans, tuition benefits, ECO pass, paid time off – vacation, sick, and holidays and more. To see what benefits are available, please visit: https://www.cu.edu/employee-services/benefits-wellness .

Diversity and Equity:

The University of Colorado Anschutz Medical Campus is committed to recruiting and supporting a diverse student body, faculty and administrative staff. The university strives to promote a culture of inclusiveness, respect, communication and understanding. We encourage applications from women, ethnic minorities, persons with disabilities, persons within the LGBTQ+ community and all veterans. The University of Colorado is committed to diversity and equality in education and employment.

Qualifications:

Minimum Qualifications:

Applicants must meet minimum qualifications at the time of hire.

• PhD in relevant scientific area such as Computational Biology, Computer Science, or Bioinformatics 

Preferred Qualifications:

• Prior experience with high-performance computing platform.
• Prior experience with high-throughput sequencing data analysis.
• Prior experience with applying or building machine learning methods.
• Prior experience managing code with a version control system (GitHub, GitLab, etc.)
• At least one first author publication or presentation at a national or international conference.
• Attributable contributions to source code

Knowledge, Skills and Abilities:

• Excellent communication and organizational skills
• Practical experience in data cleaning, wrangling, and visualization
• Practical experience in deployment of machine learning models on real data
• Evidence of working on collaborative and interdisciplinary teams
• Demonstrated willingness to give/take constructive criticism and to sustain a supportive and inclusive lab environment 

How to Apply:

For full consideration, please submit the following document(s):

Applications are accepted electronically ONLY at www.cu.edu/cu-careers .

Questions should be directed to: Olivia Castillo at [email protected]

Screening of Applications Begins:

Screening begins on 9/1/2024  

Anticipated Pay Range:

The starting salary range (or hiring range ) for this position has been established as HIRING RANGE:

$70,000 – $75,000

The above salary range (or hiring range ) represents the University’s good faith and reasonable estimate of the range of possible compensation at the time of posting. This position is not eligible for overtime compensation unless it is non-exempt.

Your total compensation goes beyond the number on your paycheck. The University of Colorado provides generous leave, health plans and retirement contributions that add to your bottom line.

Total Compensation Calculator: http://www.cu.edu/node/153125

ADA Statement:

The University will provide reasonable accommodations to applicants with disabilities throughout the employment application process. To request an accommodation pursuant to the Americans with Disabilities Act, please contact the Human Resources ADA Coordinator at [email protected] ​.

Background Check Statement:

The University of Colorado Anschutz Medical Campus is dedicated to ensuring a safe and secure environment for our faculty, staff, students and visitors. To assist in achieving that goal, we conduct background investigations for all prospective employees.

Vaccination Statement:

CU Anschutz strongly encourages vaccination against the COVID-19 virus and other vaccine preventable diseases . If you work, visit, or volunteer in healthcare facilities or clinics operated by our affiliated hospital or clinical partners or by CU Anschutz, you will be required to comply with the vaccination and medical surveillance policies of the facilities or clinics where you work, visit, or volunteer, respectively. In addition, if you work in certain research areas or perform certain safety sensitive job duties, you must enroll in the occupational health medical surveillance program .