********************PostDocs******************** The Pfeifer Lab (spfeiferlab.org) at Arizona State University is searching for a Postdoc to investigate the fine-scale changes in rates of mutation and recombination through evolutionary time within the primate clade. Projects will involve computational methods development as well as analyses of large-scale genomic data sets. Thus, the successful candidate is expected to have a strong computational and statistical background (programming proficiency in R, Perl, or Python, and shell scripting is essential; experience with analyzing high throughput sequencing data is highly desired) along with a genuine interest in genetics and biology. Preference will be given to candidates with a strong publication record, evidence of research productivity, and ability to successfully communicate scientific information. Funding is available for three years, contingent on annual renewal based on progress. The start date is flexible. The Pfeifer Lab offers a vibrant work environment with excellent opportunities for collaborative efforts as well as independent accomplishments. The Lab is integrated within a diverse bioinformatics, evolution, and population genetics research community at ASU (ASUpopgen.org), as well as the Centers for Evolution and Medicine (evmed.asu.edu) and Mechanisms of Evolution (biodesign.asu.edu/mechanisms-evolution). Additional information about the Lab and research can be found at: http://spfeiferlab.org. Interested applicants should send a short summary of research interests, CV, and contact information for two references to susanne.pfeifer@asu.edu. The evaluation of applications will begin on September 1st, 2017, and will continue until a suitable candidate has been found. Informal inquiries are welcome. Susanne Pfeifer ********************WorkshopsCourses******************** Dear all, we have the last 4 spots left for the course "Introduction to Python for biologists", 2-6 October 2017, Berlin (Germany). Application deadline is: September 2nd, 2017 Please visit our website to register : https://www.physalia-courses.org/courses-workshops/course2/ Instructor: Dr. Martin Jones (founder, Python for biologists). https://www.physalia-courses.org/instructors/t1/ Course overview Python is a dynamic, readable language that is a popular platform for all types of bioinformatics work, from simple one-off scripts to large, complex software projects. This workshop is aimed at complete beginners and assumes no prior programming experience. It gives an overview of the language with an emphasis on practical problem-solving, using examples and exercises drawn from various aspects of bioinformatics work. After completing the workshop, students should be in a position to (1) apply the skills they have learned to tackling problems in their own research and (2) continue their Python education in a self-directed way. All course materials (including copies of presentations, practical exercises, data files, and example scripts prepared by the instructing team) will be provided electronically to participants. Intended audience This workshop is aimed at all researchers and technical workers with a background in biology who want to learn programming. The syllabus has been planned with complete beginners in mind; people with previous programming experience are welcome to attend as a refresher but may find the pace a bit slow. If in doubt, take a look at the detailed session content below or drop Martin Jones (martin@pythonforbiologists.com) an email. Session content Monday 2nd - Classes from 09:30 to 17:30 Session 1 - Introduction In this session I introduce the students to Python and explain what we expect them to get out of it and how learning to program can benefit their research. I explain the format of the course and take care of any housekeeping details (like coffee breaks and catering arrangements). I outline the edit-run-fix cycle of software development and talk about how to avoid common text editing errors. In this session, we also check that the computing infrastructure for the rest of the course is in place (e.g. making sure that everybody has an appropriate version of Python installed). Core concepts introduced: source code, text editors, whitespace, syntax and syntax errors, Python versions Session 2 - Output and text manipulation In this session students learn to write very simple programs that produce output to the terminal, and in doing so become comfortable with editing and running Python code. This session also introduces many of the technical terms that we'll rely on in future sessions. I run through some examples of tools for working with text and show how they work in the context of biological sequence manipulation. We also cover different types of errors and error messages, and learn how to go about fixing them methodically. Core concepts introduced: terminals, standard output, variables and naming, strings and characters, special characters, output formatting, statements, functions, methods, arguments, comments. Tuesday 3rd - Classes from 09:30 to 17:30 Session 3 - File IO and user interfaces I introduce this session by talking about the importance of files in bioinformatics pipelines and workflows, and we then explore the Python interfaces for reading from and writing to files. This involves introducing the idea of types and objects, and a bit of discussion about how Python interacts with the operating system. The practical session is spent combining the techniques from session 2 with the file IO tools to create basic file- processing scripts. Core concepts introduced: objects and classes, paths and folders, relationships between variables and values, text and binary files, newlines. Session 4 - Flow control 1 : loops A discussion of the limitations of the techniques learned in session 3 quickly reveals that flow control is required to write more sophisticated file-processing programs, and I introduce the concept of loops. We look at the way in which Python loops work, and how they can be used in a variety of contexts. We explore the use of loops and lists together to tackle some more difficult problems. Core concepts introduced: lists and arrays, blocks and indentation, variable scoping, iteration and the iteration interface, ranges. Wednesday 4th - Classes from 09:30 to 17:30 Session 5 -Flow control 2 : conditionals I use the idea of decision-making as a way to introduce conditional tests, and outline the different building-blocks of conditions before showing how conditions can be combined in an expressive way. We look at the different ways that we can use conditions to control program flow, and how we can structure conditions to keep programs readable. Core concepts introduced: Truth and falsehood, Boolean logic, identity and equality, evaluation of statements, branching. Session 6 -Organizing and structuring code We discuss functions that we'd like to see in Python before considering how we can add to our computational toolbox by creating our own. We examine the nuts and bolts of writing functions before looking at best-practice ways of making them usable. We also look at a couple of advanced features of Python - named arguments and defaults. Core concepts introduced: argument passing, encapsulation, data flow through a program. Thursday 5th - Classes from 09:30 to 17:30 Session 7 -Regular expressions I show how a range of common problems in bioinformatics can be described in terms of pattern matching, and give an overview of Python's regex tools. We look at the building blocks of regular expressions themselves, and learn how they are a general solution to the problem of describing patterns in strings, before practising writing some specific examples of regular expressions. Core concepts introduced: domain-specific languages, modules and namespaces. Session 8 -Dictionaries We discuss a few examples of key-value data and see how the problem of storing them is a common one across bioinformatics and programming in general. We learn about the syntax for dictionary creation and manipulation before talking about the situations in which dictionaries are a better fit that the data structures we have learned about thus far. Core concepts introduced: paired data types, hashing, key uniqueness, argument unpacking and tuples. Friday 6th - Classes from 09:30 to 17:30 Session 9 -Interaction with the filesystem We discuss the role of Python in the context of a bioinformatics workflow, and how it is often used as a language to "glue" various other components together. We then look at the Python tools for carrying out file and directory manipulation, and for running external programs - two tasks that are often necessary in order to integrate our own programs with existing ones. Core concepts introduced: processes and subprocesses, the shell and shell utilities, program return values. Session 10 Optional free afternoon to cover previous modules and discuss data -- Full list of our courses and Workshops: https://www.physalia-courses.org/courses-workshops/ Best regards, Carlo -- Carlo Pecoraro, Ph.D Physalia-courses Coordinator info@physalia-courses.org http://www.physalia-courses.org/ Twitter: @physacourses mobile: +49 15771084054 https://groups.google.com/forum/#!forum/physalia-courses