Various information related to Owen Petchey's work and responsibilities at University of Zurich
Please see this web page about opportunities to work in Owen’s team. This one about how to make an (even more) effective enquiry may also be useful.
All information below is valid for Spring Semester 2025.
To take the course you must be enrolled in the course in OLAT. If you are not enrolled in the course in OLAT you will not receive communications about the course. If you are uncertain about being enrolled, please see the first question in the FAQ below.
Please see the important information in the UZH Vorlesungverzeichnis/Course Catalogue.
You may also like to view the course Learning Objectives.
How do I register for / book the course / get the relevant introductory information, even if it is after the booking deadline?
If you would like to register/book to take BIO144 then please: login on the module booking system (the link is on this page: https://www.students.uzh.ch/en/booking.html); in the module booking system of UZH, go to “Freie Modulsuche” (free search); remove the cross in the checked box “eingeschränkte Suche” (“limited search”); enter “BIO 144” in the search field; then you can register for it.
If you cannot register/book with that method, please contact studienkoordination@biol.uzh.ch
If you missed the registration period but would still like to register, please contact studienkoordination@biol.uzh.ch
If you can’t book a place on the course via the booking tool, please contact studienkoordination@biol.uzh.ch
If you are not enrolled in the OLAT course and need to be, please contact studienkoordination@biol.uzh.ch
If you missed the registration period, please make sure you do the necessary preparation for the course (see next FAQ question).
What preparation must I do before the class starts?
The course could be quite challenging, especially in the first few weeks, so its really worth doing this preparation. Before the first class, please carefully look at all of the content in these two sections in OLAT: About the course and Previous knowledge. This may take a few hours.
When do I get access to the material in OLAT?
A couple of weeks before the course starts.
Where is the material for the course?
It is all in OLAT, or linked to in OLAT.
What should I bring to class?
I can’t say everything you should bring, but you at least need to have a laptop in the first (and every other) class.
I can’t attend all of the lectures and or practicals. Can I still take the course?
Your learning is in your control in this course. Material is online and accessible at any time (after release). Lectures are recorded and available to watch after. Practical material is online also. Attendance is not monitored. However, you are strongly encouraged to attend lectures and practicals.
Do I have to attend all of the practicals?
[Same as previous answer.] Your learning is in your control in this course. Material is online and accessible at any time (after release). Lectures are recorded and available to watch after. Practical material is online also. Attendance is not monitored. However, you are strongly encouraged to attend lectures and practicals.
Is it enough to view the podcasts and not be “present” at a lecture?
[Same as previous answer.] Your learning is in your control in this course. Material is online and accessible at any time (after release). Lectures are recorded and available to watch after. Practical material is online also. Attendance is not monitored. However, you are strongly encouraged to attend lectures and practicals.
I cannot be present for lecture/practical/day/week X, Y, Z. Is possible to still take the course?
[Same as previous answer.] Your learning is in your control in this course. Material is online and accessible at any time (after release). Lectures are recorded and available to watch after. Practical material is online also. Attendance is not monitored. However, you are strongly encouraged to attend lectures and practicals.
I have another course that runs at the same time as the lecture/practicals. Can I still take the course?
In principle yes (and see the answer before this one). However, please contact please contact studienkoordination@biol.uzh.ch to highlight the conflict you have.
Can I audit the course?
Yes. Also contact studienkoordination@biol.uzh.ch and ask to be booked onto the course but as a student auditing it. This will ensure you receive any important emails about the course.
The practical training on Thursday and Friday, are we required to attend both or just select Thursday or Friday, as some of these days overlapped with my other courses?
You would be assigned to either Thursday or Friday. There is no problem, however, to switch sometimes, without letting us know. Biology studies coordination (studienkoordination@biol.uzh.ch) does the assignment.
I have no previous experience in the R program, can I also attend thee course? Will this course also teach the R program as well?
We do assume some basic R knowledge. We suggest you prepare by looking through Chapter 2 of the Insights from data book. A few weeks before the course begins we distribute other instructions to help students prepare for the course.
Can I ask a question that isn’t covered here.
Yes, but first please look at the OLAT FAQ Wiki as it has many more questions and answers collected from previous years. If you still have a question, please ask in the OLAT Discussion Forum, email if it is of a personal nature, or do so in person (online if required) during the first practical class.
Courses that might interest you after having done BIO144, that follow on in the quantitative / modelling / programming / data science realm are listed on this spreadsheet. Note that it may not be completely up to date, so please consult the UZH module directory to check for currency and also further details.
BIO 144 – Data Analysis in Biology is a 4th semester mandatory course for the approx. 350 biology, biomedicine, and other students. It is a great opportunity to impart to students the wonderful world of quantitative problem solving, in a large, interactive, and enjoyable class. We will cover getting data, managing data, visualising data, summarising data, statistical analysis (mostly linear models, but also some other methods), and communicating results. We will use the R programming language for all of this.
The course lectures are 1-3pm on Mondays, and practicals are 1-3pm Thursday (for half the students in the class) and 1-3pm Friday (for the other half) for 12 weeks (semester is 14 weeks, but two weeks involve self-study), from late February to early June. TAs are required during the practical classes. TAs can attend the lecture on Monday to help prepare them for the following week’s practical.
During the practical class, all students are in the same large room, and they work through exercises. Instructors and TAs help students with questions, and can also pro-actively offer assistance.
Some important points about TAing this course:
The TA group will largely autonomously run the practical sessions. TAs should be team oriented, keen to lead, and confident in their preparation.
It is mandatory that TAs have a deep understanding of the course material, so they can help students with the majority of questions that may be asked. This includes the statistical concepts, calculations, and methods, as well as implementation in R.
Any TA must be able and willing to present an introduction to the practical session to the whole class, and to present a summary at the end. A template will be provided.
Any single TA should work on at least six afternoons, ideally consecutive, and ideally a TA would work on both Thursday and Friday of any single week.
We provide a two hours training and familiarisation session a few weeks before the course starts. This is mandatory for all TAs. We will also provide a TA forum for discussion and questions.
All grading is done automatically by computer, so TAs can focus their time on the fun stuff: interacting and helping the students.
We will need help from a few TAs to quality control the final exam papers and to invigilate the final exams.
All time used is counted, e.g. preparing for TAing, contact hours, forum moderation, all count. TAs must keep a track of their time spent on the course; Owen will verify this at the end of the course. For reference, one might expect 4 hours preparation per week (2 hours watching the lecture and two hours for the practical session) and 2 hours for each practical session giving 48 hours for 6 weeks of TAing both afternoons or 96 hours for the whole course, plus a few hours spent in administration and TA briefing/training. Additional hours could be gained from invigilation of the final exam.
To express interest please contact Martina Jelic (email address on this web page: https://www.ieu.uzh.ch/member/current.php).
Ecology Block Course Please contact Dr Frank Pennekamp about this course. You can find his email address on this page.
Research internship in Ecology Please check the information here (ignore the mention of the masters programme in this document), and below.
If you’re interested in doing an internship with a group at UZH, please discuss with the possible supervisor. The first thing to do is think about what aspects of ecology you are interested in, to look at researchers at UZH that do ecologically oriented research, and hopefully find a match between those two. Then you should approach the researcher to see if they would consider hosting an internship.
Once you have made arrangements with your prospective supervisor, please send Prof. Petchey the following information: Supervisor name, project title, 50 word maximum project description, dates of internship, number of credit points sought, and confirmation that you understand how the module is graded. You can find his email address on this page.
In order to do an internship involving scuba diving, or other highly regulated activity, there must be written authorisation from a UZH member of staff, confirming that all necessary qualifications, insurance, and other appropriate conditions are in place. (In the recent past it was not possible to find such a person.)
Here is the grading rubric for BIO357.
Here are the regulations regarding an external research internship. There are a few things to do in order to get approval for an external research internship to contribute credit points.
Contact Prof Petchey with your idea. You can find his email address on this page.
Please have your external supervisor send an email to Prof. Petchey with the following text: “I understand that I will be responsible for all aspects of insert name of student during their Research Internship, including supporting their preparation of their final report according to the learning objectives and assessment rubric, though excluding grading of this report. I have read and understand the documents here and here. I am aware that the final report must and will be graded by a faculty member at the University of Zurich.”
Please have the external supervisor also send their CV, with information included about previous experience supervising student projects.
Please also send a ~50 word summary of the proposed research project (this can come from you or the external supervisor).
I hope that you nor your supervisors feel this is too demanding. Once we receive this information, we will let you know about approval, or whether some discussion is needed.
Important: the internship is assessed on the written report, according to the supplied rubric. Please make sure sufficient time and effort are dedicated to the written report! It is easy to fail (grade < 4.0) by submitting a poor report. The written report should be submitted at the end of the internship, and not after the internship has finished.
For enquiries, contact Owen Petchey about this course. You can find his email address on this page.
For supervisors: to complete the formalities, please send Owen this form completed and including a proposed final grade, and justification of the proposed grade based on the assessment rubric
BIO 377, Introduction to R and the Tidyverse (masters level course).
Do not take this course if you have already taken BIO144
This course runs in fall semester. Further information about the course is here. For any information about registration please contact Maja Weilenmann. You can find her email address here.
BIO 604, R-Lunch group. This course is not currently running. If you would like to help restart it, please contact Owen.
BIO633 Reproducible Research in Ecology, Evolution, Behaviour, and Environmental Studies. This course is not currently running. If you would like to help restart it, please contact Owen. Some information about it is here.
The current director of the programme, and other important information about it can be found here: PhD Programme in Ecology web page. Also please consider contacting the coordinator of the programme, Debra Zuppinger-Dingley. You can find her email address on this page.
The current Coordinator of this specialisation of the Masters in Biology can be found here: Masters Coordinator.