I am currently recruiting for a postdoc position at the University of Texas at Austin in the Department of Statistics and Data Sciences. The candidate must have a recent PhD in Statistics/Biostatistics. Residence in Austin, TX during the entirety of the postdoc will be a MUST for the position. Please read all details below. Interested candidates should email their (1) CV/resume and (2) 2 letters of reference (sent from letter-writers) to parast [at] austin [dot] utexas [dot] edu.

About

I am an Associate Professor in the Department of Statistics and Data Sciences at the University of Texas at Austin. My statistical research has focused on developing robust methods to evaluate surrogate markers, robust estimation of treatment effects, and developing and evaluating risk prediction procedures for long term survival. My applied research has focused on measuring and comparing health care quality, and survey design and analysis for health care related surveys in a variety of settings including the emergency department, inpatient hospital, hospice, and pediatric setting. Prior to joining UT Austin, I was a senior statistician at the RAND Corporation and co-director of RAND's Center for Causal Inference.

Projects (Some Examples)

1. How can we evaluate a surrogate marker when the sample size is very small e.g., less than 20 in each treatment group?

2. How can we formally test transportability from one study to another with respect to the surrogate information and strength?

3. How can we assess sensitivity to violations of the assumptions needed to evaluate a surrogate e.g., monotonicity assumption?

4. How can we evaluate a set of surrogate markers when we have multiple studies with 1-2 surrogates measured in each study, and we want to combine information across studies?

 

Research Principles

Little by little, a little becomes a lot.

Your habits should align with your goals. Your goals should align with your values.

Know your why. Why are you doing what you are doing?

If you don't value your own time, no one else will.

 

Ideal Candidate

1. Organized.

2. Receptive to feedback.

3. Knows or is willing to learn good coding hygiene and how to make R packages.

4. Passionate about applying statistical methods to health data.

5. Respectful of others, whether junior or senior to you.

6. Recognizes the value of prioritizing and doing deep work.

7. Values taking care of your mental health and self-care.

 

Expectations

1. Proficient in R and Latex.

2. Experience with survival analysis, causal inference, nonparametric methods, large-scale simulations, and applying methods to real data.

3. Experience writing manuscripts for peer-reviewed publication in statistics journals.

4. Ability to communicate statistical methods clearly.