TA positions at DIKU blocks 3 and 4 2020

Read about the assignments you are required to handle as a TA in courses at the Department of Computer Science.

General info regarding workload:
7,5 ECTS courses equal 130 hours distributed over one block
15 ECTS courses equal 260 hours distributed over two blocks

Algoritmer og Datastrukturer (AD) (BSc)

Course organiser: Christian Wulff-Nilsen, koolooz@di.ku.dk.

The TA tasks will involve weekly meetings with course organizers, bi-weekly exercise sessions with students, and correcting weekly assignments handed in by students. In the exercise sessions, the TA should help students with exercises and should also act as examiner, conducting oral trial exams for the students.

Applied Programming (APP) (MSc)

Course organiser: Sune Darkner, darkner@di.ku.dk.

The position as TA for Applied Programming requires programming solid experience with C++ (c++ 11) including templates. The TA role is to help the students during exercises 8-9 hrs a week. We run the program as a flipped class-room and at least one or both lectures will be present during class. For further information please contact Sune Darkner.

Computability and Complexity (CoCo) (MSc)

Course organiser: Christian Wulff-Nilsen, koolooz@di.ku.dk.

The tasks will be to correct hand-ins of weekly assignments and to attend exercise classes, helping students with the exercises they work on.

Computational Methods in Simulation (CMIS) (MSc)

Course organiser: Kenny Erleben, kenny@di.ku.dk.

As TA on CMIS you will be working closely together with the teachers. Your tasks will mostly be correcting students hand-ins and take part in giving input during the grading. You will help students acquire a sufficient understanding of simulation methods such that they can implement and play with these methods. Most classes are done by teachers leaving a large degree of freedom in picking one’s own work schedule, the work is extremely flexible as long as deadlines are meet.

Datalogiens videnskabsteori (VtDat) (BSc)

Kursusansvarlig: Henrik Kragh Sørensen, henrik.kragh@ind.ku.dk

Arbejdsopgaver: kontakt kursusansvarlig for information om arbejdsopgaver på kurset. Kursusbeskrivelse kan findes her.

Data Science (DS) (BSc)

Kursusansvarlig: Anders Søgaard, soegaard@di.ku.dk, & Wouter Krogh Boomsma, wb@di.ku.dk.

Data Science is a new BSc course and part of the Data Science specialisation. Teaching assistants should have have a full BSc in Computer Science and ideally knowledge of introductory Data Science; e.g, as obtained through either machine learning or data Science MSc. courses. The core topics covered in the course are: data integration, reading of structured text, databases, model design and implementation, and data exploration & visualisation.

Specific TA tasks could include:

  1. Supervision of project work of student groups during regular weekly classes.
  2. Offer exercise classes, and address student questions (both in-class and in forums).
  3. Participate in weekly TA meetings.
  4. Validate assignments and exam to provide estimates of effort to lecturers.
  5. Evaluate assignments and provide some assistance concerning exam evaluations.

Further details can be found in the course description.

Data mining og visualisering af netværksbaseret kommunikation KOM-IT (MSc)

Data Mining and Visualization of Network-Based Communication
Course organiser: Jakob Grue Simonsen, simonsen@di.ku.dk.

The course aims at providing students with the ability to explain the use of statistical models, basic data mining, and visualization to describe and predict patterns of use in IT systems and communications in (social and other) networks.

Course students are students from the humanities-based study program in Communication and IT, and have limited background in traditional computer science. They are, however, highly motivated.

TA duties include preparing for, and holding 4 hours of weekly exercise sessions, coming to short weekly TA meetings, participating in the forum on the course website, and providing feedback for a hand-in assignments. The course is taught in the spring semester (= blocks 3 and 4) at the Faculty of Humanities at the University of Copenhagen South Campus on Amager.

We need 2 TAs. Any graduate student in computer science is well-equipped to be a TA. Though machine learning per se is not taught in the course, we prefer TAs with an enthusiasm for machine learning and teaching aspects of it to enthusiastic students with a non-CS background.

Design project Kom & It (BSc)

Course organiser: Katarzyna Wac, wac@di.ku.dk.

There are +70 students organized in 2 groups: Monday (exercises 10-12) and Friday (exercises 12-14). The course goal is to design an IT-based solution for some real life problem - which the students must identify themselves along the course.

TA must prepare 2h exercises for the course each week, base for the exercises will be given by the teachers. There are 4 non-mandatory assignments during the semester. Assignments are given by the teachers and must be evaluated by TAs as well. The regular teaching weeks aside, we would like the TAs to help out in the week immediately before the course and in the exam week. The TA is expected to prepare for, and hold exercise sessions, come to weekly TA meetings (average 30 min, schedule as agreed between TAs and the teachers), participate in email correspondence about TA tasks, participate in the forum on the course website and help students outside of regular hours. 

Diskret Matematik og Formelle Sprog (DMFS)

Course organiser: Jakob Nordström, jn@di.ku.dk.

Tasks include:

  • Classroom teaching with a focus on homework assignments
  • Participation in weekly TA meetings
  • Correction of assignments

Elements of Machine Learning (BSc)

Course organiser: Martin Lillholm, grumse@di.ku.dk.

Tasks include:

  • Classroom teaching with a focus on homework assignments
  • Participation in weekly TA meetings
  • Correction of assignments

Grundlæggende statistik og sandsynlighedsregning (BSc)

Course organiser: Thomas Høgholm Jørgensen, thomas.h.jorgensen@econ.ku.dk

Tasks include

  • correcting hand-ins of assignments
  • conducting exercise classes
  • helping students with the exercises they work on

Implementation of Programming Languages (IPS) (BSc)

(Implementering af programmeringssprog (IPS))

Course organiser: Andrzej Filinski, andrzej@di.ku.dk.

TAs are expected to:

  1. hold two exercise hours weekly (and prepare for them)
  2. mark the weekly assignments and project and provide feedback to students
  3. help in preparing the project solutions and in tracking down student's progress

Information Retrieval (IR) (MSc)

Course organiser: Christina Lioma, c.lioma@di.ku.dk

Tasks include:

  • Classroom teaching with a focus on homework assignments
  • Participation in weekly TA meetings
  • Correction of assignments

Interaktionsdesign (Inter) (BSc)

Kursusansvarlig: Kasper Hornbæk, kash@di.ku.dk.

Arbejdsopgaver:

  • Gennemgå relevante tidligere eksamensopgaver ved øvelser.
  • Vejlede studerende i løsning af obligatoriske opgaver ved 2 ugentlige øvelser af 2 timer.
  • Bedømme og kommentere de studerendes besvarelser af obligatoriske opgaver.Der lægges vægt på konstruktive tilbagemeldinger.
  • Deltage i et ugentligt instruktormøde af ca. 1 times varighed.

Instruktorer skal helst have haft Interaktionsdesign eller det tilsvarende tidligere kursus ”Menneske-datamaskine interaktion”. Instruktorer skal tale og forstå dansk perfekt.

Interaktionsdesign kom & it (BSc)

Course organiser: Kasper Hornbæk, kash@di.ku.dk.

The main responsibility of the teaching assistants is to run tutorials/exercise classes with students once a week, 2 hours each. The TAs are expected to prepare themselves in advance of the tutorials; material for the tutorials including exercises and assignments has already been prepared for the TAs. In addition, TAs are expected to assess weekly assignments (pass/fail), of which students have to hand in 5 in the entire semester.

We will need 2 TAs for the course. During regular teaching weeks, the TA is expected to devote 5-10 hours to TA tasks.

The TAs are expected to prepare for, and hold exercise sessions, come to weekly TA meetings, participate in the forum on the course website and help students outside of regular hours. In connection with admitting students to the exam, TAs are expected to help with correcting and approving homework assignments.

Introduction to Data Science (IDS) (MSc)

Course organizer: François Lauze, francois@di.ku.dk.

The work load will be up to 135 hours in total (approximately 15 hours per week).

The tasks include:

  • Classroom teaching with a focus on homework assignments
  • Participation in weekly TA meetings
  • Correction of assignments
  • Test-computation of assignments.

Applicants should be strong on the fundamentals of data science and enjoy the challenge of teaching motivated students with very variable backgrounds.

Large-Scale Data Analysis (LSDA) (MSc)

Course organiser: Fabian Christian Gieseke, fabian.gieseke@di.ku.dk.

Almost every scientific and industrial field is nowadays faced with massive amounts of data and analysing these data has become a key driver of research and innovation. Taking advantage of this data-rich situation often requires specialized approaches, tools, and skills. What society needs is qualified experts capable of designing, developing, and applying data analysis techniques in the context of big data scenarios. That is, “Data Analysts” are needed and the goal of this course is to educate such experts.

In comparison to other courses dealing with machine learning or data analysis, the focus of this course is on the peculiarities of processing large amounts of data - that is, on Big Data.

The course might also be relevant for students from, among others, the studies of Computer Science, Cognition and IT, Bioinformatics, Physics, Statistics, and other areas of quantitative studies.

The course covers a selection of the following (tentative topic) list:

  • Fundamentals of large-scale data analysis
  • Large-scale machine learning
  • Deep learning
  • Parallel and distributed data analysis

Mikroøkonomi A (BSc)

Course organiser: Michael Allan Ribers, michael.ribers@econ.ku.dk

Tasks include:

  • correcting hand-ins of assignments
  • conducting exercise classes
  • helping students with the exercises they work on

Proactive Computer Security (PCS) (MSc)

Course organizer: Ken Friis Larsen, kflarsen@di.ku.dk.

The lion’s share of the TA work consists of preparing for and holding weekly lab/exercise sessions and grading and giving feedback on the weekly hand-in of assignments.

Furthermore the TAs are expected to help out well in advance of the course with planning of the curriculum, forming of exercises, assignments and tutorials as well as other  miscellaneous tasks. The TAs are also expected to be available in the week following the exam week as well as three weeks after the exam for helping out with practical tasks in connection with the grading.

TAs are expected to devote 10-15 hours to TA tasks per week. TA tasks include:

  • Design tutorials to be used during the lab sessions and published on the course website.
  • Help design and dry-run exercises and assignments.
  • Prepare for and hold lab sessions.
  • Grade and give feedback to weekly hand-in of assignments.
  • Attend weekly meetings.
  • Participate in e-mail correspondence about TA tasks.
  • Be active (and helpful) on the course website forums.
  • Help students outside of regular working hours.

Programming Language Design (PLD) (BSc)

Course organiser: Torben Æ. Mogensen, torbenm@di.ku.dk.

The TAs should handle class-room exercises (4h/week) and help evaluating the three hand-ins, of which two are theoretical and one an implementation exercise. Additionally, the TAs are expected to participate in a weekly teacher/TA meeting.

It is expected that the TAs have previously followed a compilers course (such as "Oversættere") and Advanced Programming, or equivalent. TAs who have taken "Semantics and Types" or "Advanced Language Processing" will be preferred.

Projektstyring og kravspecificering (KOMIT) (BSc)

Kursusansvarlig: Jacob Nørbjerg, jacobn@di.ku.dk.

Kurset er en let revideret udgave af faget ‘Modellering og systemudvikling’ på bacheloruddannelsen i Kommunikation og it.

Instruktorernes opgaver inkluderer:

  • Undervisning af øvelseshold, herunder især hjælp med hjemmeopgaver
  • Retning af hjemmeopgaver
  • Deltagelse i et ugentligt instruktormøde

Vi får brug for 1-2 instruktorer.

Kurset varer et semester (blok 3+4). Der er 1 øvelsestime om ugen pr. hold. I undervisningsugerne, forventes det, at en instruktor kan bidrage med ca. 10 timer om ugen. Instruktorerne forventes at forberede sig til og afholde øvelsestimer, komme til ugentlige instruktormøder og deltage i mailkorrespondance om hjemmeopgaver mv.

Tag kontakt med kursusansvarlig for mere information.

Randomized Algorithms (RA) (MSc)

Course organiser: Jacob Holm, jaho@di.ku.dk.

The TA tasks will involve mainly correcting exercises (about 10 hours a week). Optionally, you can also do the exercise class (2 hours together) a week.

More info about the course.

Randomiserede algoritmer til dataanalyse (RAD) (MSc)

Course organiser: Mikkel Thorup, mthorup@di.ku.dk.

The TA tasks will involve:

  • meetings with course organizers at most once a week,
  • bi-weekly exercise sessions with students, and correcting weekly assignments handed in by students


In the exercise sessions, the TA should help students with exercises. 

Signal and Image Processiong (SIP) (MSc)

Course organiser: Kim Steenstrup Pedersen, kimstp@di.ku.dk.

The TA tasks are:

  • Lead the exercise sessions and help students solve exercises
  • Grade and give feedback on students solutions to exercises

Software Engineering (SE) (MSc)

Course organiser: Tijs Slaats, slaats@di.ku.dk.

Course Description
The Software Engineering course focusses on the practical aspects of running a large scale software development process, including project management, requirements elicitation, software design and testing. The course is centered around a large scale software development project that is undertaken by the class as a whole.

Responsibilities
The teaching assistants are expected to take on the following responsibilities:

  • Supervision of project work by student groups during regular weekly classes.
  • Address student questions (both in-class and in forums).
  • Participate in weekly TA meetings with the course coordinator.
  • Evaluate the progress of student groups based on regular handins.

Requirements
We will need 2 TAs for the course. During regular teaching weeks, the TA is expected to devote approximately 5-10 hours to TA tasks. An ideal candidate has followed the software engineering course before, but a similar course or professional experience with large software projects may be an adequate alternative.

Softwareudvikling (SU) (BSc)

Softwareudvikling – Boris Düdder, boris.d@di.ku.dk.

Tasks include:

  • helping in preparing group projects and associated weekly exercises;
  • supervising weekly exercise sessions (one 4 hour session/week);
  • participating in maintaining course web site, including discussion forum;
  • supporting students interactively online and during ad-hoc office hours;
  • attending the weekly instructors' meeting (1 hour/week)
  • reviewing and commenting weekly/biweekly group project deliverables and final reports

Work load per TA: approx. 15 hours per week, up to 135 hours in total.

Sundheds-it infrastruktur (MSc)

Course organizer: Tariq Osman, tariq@di.ku.dk.

Tasks include:

  • støtte studerende i gruppearbejde
  • analyse af cases om sundheds-it infrastruktur
  • hjælpe med litteratursøgning
  • afholde workshops
  • rette opgaver

Systemudvikling (BSc)

Course organizer: Tariq Osman, tariq@di.ku.dk.

Tasks include:

  • støtte studerende i gruppearbejde
  • afholde workshops
  • rette opgaver

Udvikling af informationssystemer (UIS) (BSc)

Course organiser: Marcos A. Vaz Salles, vmarcos@di.ku.dk.

CS-students who are good programmers with solid experience in DB- & web programming combined with an interest in supporting the student groups & working on defining and developing smaller, realistic applications in collaboration with users outside the university. Thus communication skills and project consulting/management skills are also important.

The main tasks for teaching assistants in Development of Information Systems (UIS) are:

  1. Supervision of project work of student groups during regular weekly classes.
  2. Offer exercise classes, and address student questions (both in-class and in forums).
  3. Participate in weekly TA meetings.
  4. Validate assignments and exam to provide estimates of effort to lecturers.
  5. Evaluate assignments and provide some assistance concerning exam evaluations.

Web Science (WS) (MSc)

Course organiser: Christina Lioma (c.lioma@di.ku.dk)

Tasks include:

  • Classroom teaching with a focus on homework assignments
  • Participation in weekly TA meetings
  • Correction of assignments