NatSCA Digital Digest

  

Welcome to the weekly digest of posts from around the web with relevance to natural science collections. We hope you find this useful and if you have any articles that you feel would be of interest, please contact us at blog@natsca.org

1. Job: Curator/Lecturer in Vertebrate Palaeontology

It’s your last chance to get your applications in for this one.

Deadline: 3 April 2015

Employer: University of Cambridge

Synopsis

We seek to recruit an outstanding scientist to join the staff of the Department and Museum of Zoology at Cambridge. The successful candidate will combine excellence in research with a commitment to teaching at both undergraduate and graduate levels. In addition he/she will have the ability to engage with the work of the Museum in collections development, outreach and public engagement. 

We seek a candidate with the ambition and ability to fund and lead a world-class research group. For this post, we are likely to appoint a candidate whose research is collections-based. The appointee…

Read more and apply here

2. Exhibition: Coral Reefs

When: 27 Mar 2015 – 13 Sep 2015

Synopsis

Now opened at the Natural History Museum, London. This spectacular window into a world that enriches our very existence is well worth visiting.

Click here for more details

3. Workshop: R Without Fear – Applied R for Biologists

this course is not organised by NatSCA but it could come in handy for our members.

when: 21-25 Sep 2015
where: Facilities of the Centre de Restauració i Interpretació Paleontologica, Els Hostalets de Pierola, Barcelona (Spain).

Synopsis
Introduction to the R working environment.
– Variable types in R.
– Statistical populations and samples through working examples.
– Measurements of central tendency and variability.
– Precision, accuracy and bias.
– Hypothesis testing: Falsability, Type-I and II errors and statistical power.
– Correlation and simple regression.
– P-value vs. effect magnitude.
– Linear Models: Residuals, assumptions and interpretation.
– Explained vs. unexplained variance of a model (the coefficient of determination).
– Building functions in R.
– Introduction to graphics in R.
– The concept of partial effect: Partial regression and correlation.
– General Linear Models (GLM).
– Curve fitting in linear models and General Additive Models (GAMs).
– The problem of spatial autocorrelation in ecology and evolution.
– Multicolinearity: When is there a problem?
– Additive vs. multiplicative effects: Checking and plotting interactions.
– Introduction to General and Generalized Linear Mixed Models (GLMM).
– Fixed vs. Random effects and implications for analysis: Main R functions.
– Introduction to Bayesian statistics: The function MCMCglmm.
– Practical examples in evolutionary ecology:
The study of natural selection.
Applications of linear models for quantitative genetics.
– Student’s case studies.

for more information visit their website

Compiled by Sam Barnett, NatSCA Blog Editor

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