This version of the course guide is provisional until the period for editing the new course guides ends.

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Professional Practice

Code: 42400 ECTS Credits: 15
2025/2026
Degree Type Year
Bioinformatics OB 0

Contact

Name:
Marta Puig Font
Email:
marta.puig@uab.cat

Teachers

Antoni Barbadilla Prados
Leonardo Pardo Carrasco
Miquel Àngel Senar Rosell
Jean Didier Pierre Marechal
Angel Gonzalez Wong
Jaime Martinez Urtaza
Laura Masgrau Fontanet
Alex Peralvarez Marin
Marta Puig Font
Sònia Casillas Viladerrams
Maria Cinta Pegueroles Queralt
Marc Torrent Burgas
Xavier Daura Ribera

Teaching groups languages

You can view this information at the end of this document.


Prerequisites

To carry out this module it is necessary to have passed previously both compulsory modules (Programming in Bioinformatics and Core Bioinformatics) and one of the optative modules.

It is recommended you have a Level B2 of English or equivalent.


Objectives and Contextualisation

The main objective of these practices is to promote the students’ interaction with the professional and research environments around them.


Competences

  • Apply research results to obtain new good and services valuating their industrial and commercial viability to transfer them to society.
  • Assess gender inequalities when acting in this field of knowledge.
  • Conceive, design and carry out scientific, technical or industrial projects in biocomputing and be able to interpret and extract knowledge from them.
  • Design and apply scientific methodology in resolving problems.
  • Identify the biocomputing needs of research centres and companies in the biotechnology and biomedicine sectors.
  • Possess and understand knowledge that provides a basis or opportunity for originality in the development and/or application of ideas, often in a research context.
  • Propose biocomputing solutions for problems deriving from omic research.
  • Propose innovative and creative solutions in the field of study
  • Students should be able to integrate knowledge and face the complexity of making judgements based on information that may be incomplete or limited and includes reflections on the social and ethical responsibilities associated with the application of their knowledge and judgements
  • Students should know how to apply the knowledge they have acquired and their capacity for problem solving in new or little known fields within wider (or multidisciplinary) contexts related to the area of study
  • Students should know how to communicate their conclusions, knowledge and final reasoning that they hold in front of specialist and non-specialist audiences clearly and unambiguously
  • Use and manage bibliographical information and computer resources in the area of study
  • Work individually and as part of a team in an international and multidisciplinary context.

Learning Outcomes

  1. Analyze bioinformatics cases and propose innovative solutions.
  2. Apply knowledge and skills acquired in genomics, proteomics and computation to potential technological research or business projects based on biocomputing.
  3. Apply research results to obtain new good and services valuating their industrial and commercial viability to transfer them to society.
  4. Assess gender inequalities when acting in this field of knowledge.
  5. Design and apply scientific methodology in resolving problems.
  6. Possess and understand knowledge that provides a basis or opportunity for originality in the development and/or application of ideas, often in a research context.
  7. Propose business projects in the area of biocomputing from an integrated view of R&D processes.
  8. Propose innovative and creative solutions in the field of study
  9. Select critically and apply in each case, appropriate bioinformatics tools to the problem.
  10. Students should be able to integrate knowledge and face the complexity of making judgements based on information that may be incomplete or limited and includes reflections on the social and ethical responsibilities associated with the application of their knowledge and judgements
  11. Students should know how to apply the knowledge they have acquired and their capacity for problem solving in new or little known fields within wider (or multidisciplinary) contexts related to the area of study
  12. Students should know how to communicate their conclusions, knowledge and final reasoning that they hold in front of specialist and non-specialist audiences clearly and unambiguously
  13. Use and manage bibliographical information and computer resources in the area of study
  14. Use clear, concise communication to assess and guide the interpretation of data for resolving problems in the biomedical field.
  15. Work individually and as part of a team in an international and multidisciplinary context.

Content

During the internship, the student will be closely monitored by the research tutor in the company/research center where they are receiving the practical training.

In this module, the student will have the opportunity to collaborate in research projects, applying all the knowledge obtained throughout the course, and gaining professional experience.

In the professional practice module can include some visits to research centres and institutions working in the field of bioinformatics. The aim of these visits is to show to the students the research and professional environments around bioinformatics and some of the job positions which they will be able to apply for once they have finished the MSc in Bioinformatics.


Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Supervised      
Practical training 375 15 4, 1, 2, 3, 14, 5, 7, 8, 11, 12, 10, 9, 6, 15, 13

The Professional Practice is a mandatory module that involves 375 hours of student work within a company or a research group. The students may choose to do the internship in a research center, if they are planning in the future to engage in basic research, or in private companies or hospitals to develop the career in applied fields.

During the first semester, the module coordinator will give a list with offers from companies and institutions for the MSc in Bioinformatics students. The students can choose based on their preferences among the available projects in the offered list and the coordinator will ensure proper communication between the student and the responsible person in the company or institution.

If the student wants to do their internship in a company or institution outside of those in the provided list, the student will need to deliver a description of the project and the institution information so that the proposal can be evaluated by a comission.

It is the student’s responsibility to find the company or research group where they will do the professional practice.

Once found, they must communicate it to the module coordinator and complete the required form to establish an agreement between the UAB and the institution.

The module coordinator will assign an academic tutor from the UAB who ensures the correct development of the student's internship. Once the form has been completed and signed, the student will deliver the form to the Academic Administration office of the Faculty of Biosciences at least 1 month before the beginning of the internship. After that, the Academic Administration staff will get in touch with both the student and the responsible person at the company/institution to have the final agreement signed.

 

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.


Assessment

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Student's practice report 30% 0 0 4, 1, 2, 3, 14, 5, 7, 8, 11, 12, 10, 9, 6, 15, 13
Tutor's follow-up and evaluation report 70% 0 0 4, 1, 2, 3, 14, 5, 7, 8, 11, 12, 10, 9, 6, 15, 13

The Professional Practice Module will be evaluated using a follow-up and evaluation report, written by the project supervisor at the institution/company (70%) and with the grading of the student’s practice report (30%).

The student must ensure that the module coordinator receives both documents, practice report and tutor's evaluation report.

Students will obtain the grade of "Not assessed" when the evaluated activities have a weight of less than 67% in the final grade.

Use of AI

For this subject, the use of Artificial Intelligence (AI) technologies is allowed exclusively in support tasks, such as bibliographic or information search, text correction or translations. The student must identify clearly which parts have been generated with this technology, specify the tools used, and include a critical reflection on how they have influenced the process and the final result of the activity. Non-transparency of the use of AI in this activity or its use for tasks where this is not allowed will be considered a lack of academic honesty and may result in a partial or total penalty in the grade of the activity, or greater penalties in serious cases.


Bibliography

The student will be responsible for the research and consulting literature required to perform their practice. Their supervison may help them.

Recommended lectures

  • Nussbeck, S.Y., Weil, P., Menzel, J., Marzec, B., Lorberg, K. & Schwappach, B. 2014 The laboratory notebook in the 21st century: The electronic laboratory notebook would enhance good scientific practice and increase research productivity. EMBO reports 2014 15: 631-4
  • Bosch, X. 2010 Safeguarding good scientific practice in Europe. EMBO reports 2010 11: 252-7

 


Software

Software will depend on the practices performed by the student.


Groups and Languages

Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.

Name Group Language Semester Turn
(PEXTinternm) Pràctiques externes i pràcticum amb supervisió interna (màster) 99 English second semester morning-mixed
(PEXTm) Pràctiques externes i pràcticum (màster) 1 English second semester morning-mixed