Hi all,I have a couple of queries for your good selves. My background is in physics (BSc Hons.) and electrical/nuclear engineering, and I'm just about to complete a doctorate (Eng.D*) focused heavily on applied machine learning techniques in the energy industry. Throughout my studies, I've worked extensively in ML and have good experience in developing techniques with R, Java and MATLAB. With this in mind, I'm looking at taking my skills and applying them to a potential career in quantitative finance.In looking at some of the advertised positions, I've noticed a few HH agencies are looking for 'machine learning quants', 'big data quants' or similar, with fairly general job descriptions and very little in terms of solid requirements, even for quantifiable skills like programming. This is in contrast to the rest of the reading I've done on these forums and beyond, where there seems to be a quite well-defined path for a good quant candidate as the competition is fierce.(1) Do these 'machine learning' or 'big data'-focused quant positions even exist, where I'd perhaps compare more favourably against the competition with my experience? I get the feeling that without formal qualifications or experience in the topics covered in, say, MFE programmes, I'd struggle to compete with even the average candidates for the vast majority of quant roles at this minute. Are these positions just HH agencies mining for CVs with buzzwords? Some of the descriptors even stipulate that experience in finance isn't mandatory, just an interest to solve problems, which seems ludicrous.(2) My school - University of Strathclyde - is respected in terms of engineering, but not so much generally in the UK. Would I not even be considered for roles when placed against Oxbridge, LSE and Imperial candidates? If so, would it be worth my while pursuing an MFE or similar in order to improve my qualifications?* For clarity, the Eng.D (short for engineering doctorate) is a doctoral-level scheme equivalent to the PhD. Essentially, it's PhD in engineering with a strong industrial component, working closely with a sponsoring company who benefit directly from the research.Cheers for your time.