From: Don Armstrong <don@donarmstrong.com>
Date: Sun, 15 Oct 2017 19:19:06 +0000 (-0700)
Subject: add laboratory science for oracle
X-Git-Url: https://git.donarmstrong.com/?a=commitdiff_plain;h=refs%2Fheads%2Fjobs%2Foracle_cancer_data_scientist;p=resume.git

add laboratory science for oracle
---

diff --git a/dla-resume.org b/dla-resume.org
index 4c9717b..7f88ba1 100644
--- a/dla-resume.org
+++ b/dla-resume.org
@@ -38,41 +38,44 @@
 + *PhD* in Cell, Molecular and Developmental Biology
 + *BS* in Biology
 * Skills
+** Laboratory Cancer Experience
++ Antibody-based methods (Westerns, immunohistochemistry, ELIZA)
++ RNA quantification (RT-PCR, Northern)
++ Cell mobility assays
++ Cell Culture (primary brain endothelial cells, U87, A172, Jurkat,
+  NIH-3T3)
 ** Genomics and Epigenomics
 + *NGS* and array-based Genomics and Epigenomics of complex human
-  diseases using *RNA-seq*, targeted DNA sequencing, *RRBS*, Illumina
-  bead arrays, and Affymetrix microarrays from sample collection to
+  diseases using *RNA-seq* and *RRBS* from sample collection to
   publication.
-+ Reproducible, scalable bioinformatics analysis using make,
-  *nextflow*, and *cwl* based workflows on cloud- and cluster-based
-  systems on terabyte-scale datasets
-+ Alignment, annotation, and variant calling using existing and
-  custom-written software, including *GATK*, *bwa*, *STAR*, and
-  *kallisto*.
-+ Correcting for and experimental design to overcome multiple
-  testing, confounders, and batch effects using Bayesian and
-  frequentist methods approaches
++ Reproducible, scalable analysis using make, *nextflow*, and *cwl*
+  workflows on cloud- and cluster-based systems
++ Alignment, annotation, and variant calling using *GATK*, *bwa*,
+  *STAR*, and *kallisto*.
+# + Correcting for and experimental design to overcome multiple
+#   testing, confounders, and batch effects using Bayesian and
+#   frequentist methods approaches
 # + Using evolutionary genomics to identify causal human variants
 ** Statistics
 + Statistical modeling (regression, inference, prediction, and
-  learning in very large (> 1TB) datasets)
+  learning in large (> 1TB) datasets)
 + Addressing confounders and batch effects
 # + Reproducible research
 ** Big Data
 + Parallel and Cloud Computing (slurm, torque, AWS, OpenStack, Azure)
 + Inter-process communication: MPI, OpenMP
 + Filestorage: Gluster, CEFS, GPFS, Lustre
-+ Linux system administration
+# + Linux system administration
 ** Mentoring and Leadership
 + Mentored graduate students and Outreachy and Google Summer of Code
   interns
 + Former chair of Debian's Technical Committee
-+ Head developer behind https://bugs.debian.org
+# + Head developer behind https://bugs.debian.org
 ** Software Development
 + Languages: perl, R, C, C++, python, groovy, sh, make
 + Collaborative Development: git, travis, continuous integration,
   automated testing
-+ Web, Mobile: Shiny, jQuery, JavaScript
+# + Web, Mobile: Shiny, jQuery, JavaScript
 + Databases: Postgresql (PL/SQL), SQLite, Mysql, NoSQL
 + Office Software: Gnumeric, Libreoffice, \LaTeX, Word, Excel,
   Powerpoint