Hey guys, I am someone from the non-technical background and have trying to get a full time role as an ML engineer for some time now. But I have realised the market is pretty much flooded with applicants and I don't have the necessary corporate experience in the domain to be considered. So I think it is wise to work as an intern first and then start from there.

So coming to my question now. What is the scenario like for internship opportunities specially in a remote setting? I feel I have the necessary skillset for atleast a junior level role so internship ideally should be gettable.

Would appreciate your views on this.

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Hi everyone,

I wanted to for advice as I started looking for jobs and realised I need a concrete plan about what I want to do so I wish you could help me a bit. I am from the EU. I started applying to around 30-40 companies but got only 1 interview for ML still in progress. I have like 5 months or more to find a job. For now, I looked in Belgium but tbh I dont want to stay here for long(weather, taxes). I plan to apply for jobs in Germany, the Netherlands, Poland(my origin country) and Switzerland(I love mountains and nature but never was there). I look for the most growth opportunities and life quality.

I feel like I need to decide what type of specialization I want to have in like 5 years. And reevaluate my learning priorities to get good starting jobs to provide more value to my profile.

I also look for nice resources to track what happening in the field or what professional ML code should look like.

Intro:

I was a Robotic/engineer for 2 years after my BSc, but I find ML/programming very cool. I wanted to know how the math and algorithms predict all of these things. I started learning myself and applied for an MSc. I got an MSc in CS.

Now I am finishing it and got a good job in Data science that was well paid but I decided to not follow it as there was no ML. I have a part-time job in the AI lab at my uni for now.

I also got a Ph.D. offer in the lab where I can do ML but I feel like it's in a domain I am not a fan of and it's quite a long commitment as I worked 2 years between BSc and MSc.

Skills:

- Mainly programming in Python got courses in Scala(I like it but need to practice more) and Java(was quite okay with it but not used a lot). Also know a bit: SQL, MATLAB, C#, C++, HTML, CSS

- I used PyTorch, SciPy, and Keras. I feel confident in SciPy I practice my pytorch to implement models as I could have more understanding regarding it. Used gymnasium for Reinforcement Learning Course. I use and for visualisation and hyperoptimization as I find it nice for the thesis and as a skill to learn.

- Maybe I am lacking here I know map reduction but I dont use Hadoop, Docker, or BiqQUery like once for a project

What I like/feel like focusing on:

- enjoyed the Reinforcement Learning Course and Scala but I dont have much experience here. We do a lot of medical-related ML projects also which feels like contributing. I like Robotics also. Do also VQA which was cool (NLP part especially).

- I look for clean ML jobs like 80% ml 20 % research, no SQL queries(could make it a bit), making SMTH useful, easily used, small dashboard draft of what it feels like. I also have no problem with cleaning and understanding data.

- read a bit about SAP in ML but do not understand what this type of work looks like.

I only find a few jobs related to this and they require like 2-3 years at least of experience or PhD/research experience.

My plan:

- Working on this part-time job and focusing on a Thesis related to Deep Learning that should be published to get some bonus points later for job hunting.

- In my free time I focus on strong Python skills, coding exercises on Exercism(Python, really rarely Scala), and doing Coursera Machine Learning Specialization and Deep Learning | Coursera when noting and understanding all things and making some flashcards second brain in obsidian for ML practices and so on. Further, I do a bit https://www.coursera.org/learn/deep-neural-networks-with-pytorch/home/welcome but I decided to stop it and do last to get strong fundamentals in knowing all machine learning models first.

- All of this is to prepare me to recreate papers from high-impact machine learning journals and document them in the form of video to attach them to my future CV.  I also like the idea of doing projects and documenting them for fun but I dont find time to do that.

My weakness:

- I dont use at all AWS, SPARK, Azure, Snowflake, and Hadoop

- I forget some ML things from courses and feel like my math understanding could be better, hence why I focus on these skills.

- improving my Pytorch skills

- no project on GitHub as I picked courses to have projects everywhere for hands-on experience but I can't publish them, maybe an interview with HR but could be a legal issue. Dont have much time now to do some just for this purpose.

- my code could be better which is why I took a Software Architecture course in Scala, in my uni they are always happy with my code but in the industry, it is probably not acceptable.

Quite a long post I tried to make it as concise and understandable as possible.

If you have any advice regarding anything above I would appreciate any feedback.

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I want to create a knowledge graph of all the dishes in the world. This knowledge graph should give me information like:-

Indian dish -> North Indian dish -> Mughlai dish -> Chicken Tikka

Italian dish -> Pizza -> Thin Crusted Margherita Pizza

Any other information that this graph may also be able to give like a description for the dish and an image is also welcome.

Currently one way I am thinking of doing this is through scraping a bunch of dish-related sites and feeding all that unstructured data to Neo4j + LLMs to build the graph.

Another approach is to use some algorithm or model to make synthetic data and then further make a knowledge graph out of that.

Please guide me on how to collect the data, build the knowledge graph or tell me about any insights that you may have.

I am to create a dataset that has all of world's dishes (By dishes I mean things like Chicken tikka, Thin Crust Margherita Pizza, Classic Margherita Pizza. It should include the dish along with all its variances).

Now I am to build a model that can tell the categorical hierarchy of the dish when I enter its name. For example if I enter Chicken Tikka it should tell me: Indian -> North Indian -> Mughlai -> Chicken tikka

I was given a hint that researching on Knowledge Graphs might help in building the model.

Can anyone give me more insights on how to go about making it?

Hello,

I'm currently recruiting a 2nd Research Fellow postions in ML centric health informatics as part of a large project on Motor Neuron Disease. Details are below. This could be suitable for people either with a background in Health Data or with strong image processing expereience -- particularly with respect to applying domain adapation and transfer learning to target domains with low volumes of positive data examples -- this is a rare disease.

The closing date of applications is this Friday the 29th of March.

Postdoctoral Research Fellow (Data Science) In Health Informatics for the Precision-ALS Project

Salary: €61,318

Initial funding for 2 Years with extension to 3 yearsClosing Date: 8

TU Dublin are currently hiring a Research Fellow in Data Science / Health Informatics for the Precision-ALS Project. Precision-ALS is a multi-year, multi-national research effort to develop computational methods to support medical treatment development for Amyotrophic Lateral Sclerosis (ALS) – the most common from of motor neuron disease. The project is developing platforms for data collection and analysis, and supporting researchers across Europe in fighting this devastating disease. The current role is for research scientists to work on the data modelling of ALS patient data to further understanding of outcome analysis, methods for patient cohortisation, and non-hypothesis driven data analysis. The post holder may also work in partnership with others on specific modality data and on the challenges associated with model adaption with respect to different clinical settings and patient cohorts.

Copy of Full Job Specification: https://drive.google.com/file/d/1v6AIAQVK97VIazmdReUzLoB1YuoZhlLo/view?usp=drive_link

Application Portal (also includes job spec): https://www.tudublin.ie/explore/jobs/current-vacancies/

Vacancy Number: 032803

About the P-ALS Project: https://www.precisionals.ie/

For further information about this post please contact: Robert Ross at robert.ross@tudublin.ie