The College of New Jersey
Data Science · California
Research Staff
Phd
Position & institution
- What is the name of your institution?
- The College of New Jersey
- Which department or unit is hiring?
- Data Science
- Which U.S. state is the position located in?
- California
- What category of position is this?
- Research Staff
- What is the official job title?
- Bioinformatics Scientist
- How would you like to present compensation?
- Salary Range
- What is the minimum of the salary range (annual)?
- $71,000
- What is the maximum of the salary range (annual)?
- $85,000
- Summarize benefits offered (health, retirement, relocation, etc.).
- Competitive benefits including retirement contributions, wellness programs, and a startup package for lab setup.
- Which application materials are required?
- Transcripts, Publications Sample, Teaching Statement, Cover Letter
- How many references / recommendation letters are required?
- 1
- When should reference letters be submitted?
- Shortlist Only
- Who is the search committee chair or primary contact?
- Prof. Samuel Müller
- What is the contact email for inquiries?
- james.kim@institute.edu
- What is the application deadline?
- 2026-10-10
- Will applications be reviewed on a rolling basis?
- No
- What is the expected start date?
- 2027-02-22
- Include your institution's standard EEO/diversity statement?
- Yes
Candidate requirements
- What is the field or area of specialization sought?
- Spatial Statistics
- What is the minimum required degree?
- Phd
- Must the degree be completed by the start date?
- No
- What is the expected teaching load (courses per year)? Enter 0 if none.
- 3
- Briefly describe teaching responsibilities and any specific courses.
- Contribute to the statistical theory and inference core and develop an elective in your area (Bayesian methods, causal inference, etc.).
- Describe research expectations (e.g., external funding, lab, publications).
- Lead the statistical design and analysis of collaborative clinical and translational studies while building an independent methods program.
Discussion
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